diff --git a/grobid-home/models/segmentation/model.wapiti b/grobid-home/models/segmentation/model.wapiti index 7683efb038..13f1d50656 100644 --- a/grobid-home/models/segmentation/model.wapiti +++ b/grobid-home/models/segmentation/model.wapiti @@ -1,4 +1,4 @@ -#mdl#2#13683 +#mdl#2#15090 #rdr#111/32/0 12:u00:%x[-4,0], 12:u01:%x[-3,0], @@ -137,7 +137,7 @@ 6:, 7:I-, 5:, -#qrk#2209968 +#qrk#2213298 8:u00:_x-4, 8:u01:_x-3, 8:u02:_x-2, @@ -1585038,6 +1585038,3825 @@ 12:u02:15:R183., 12:u01:15:R183., 12:u00:15:R183., +9:u04:SDXL:, +10:u06:Dustin, +8:u07:Zion, +8:u08:Kyle, +10:u06:Podell, +9:u08:Lacey, +9:u12:sdxl:, +10:u14:dustin, +7:u22:SDX, +8:u23:SDXL, +9:u03:SDXL:, +10:u05:Dustin, +8:u06:Zion, +8:u07:Kyle, +10:u05:Podell, +9:u07:Lacey, +13:u08:Blattmann, +9:u11:sdxl:, +10:u13:dustin, +8:u14:zion, +9:u02:SDXL:, +10:u04:Dustin, +8:u05:Zion, +8:u06:Kyle, +10:u04:Podell, +9:u06:Lacey, +13:u07:Blattmann, +12:u08:Dockhorn, +9:u10:sdxl:, +10:u12:dustin, +8:u13:zion, +8:u14:kyle, +8:u23:Dust, 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+7:u23:E.1, +16:u00:seed-setting, +7:u03:E.1, +8:u06:(P2), +9:u04:asses, +12:u07:prompts., +7:u11:e.1, +8:u14:(p2), +7:u02:E.1, +8:u05:(P2), +9:u03:asses, +12:u06:prompts., +7:u10:e.1, +8:u13:(p2), +12:uI2:()[],---, +7:u01:E.1, +8:u04:(P2), +9:u02:asses, +12:u05:prompts., +8:u12:(p2), +7:u22:(P2, +8:u23:(P2), +12:uI1:()[],---, +7:u00:E.1, +8:u03:(P2), +14:u08:Midjourney, +9:u01:asses, +12:u04:prompts., +8:u11:(p2), +12:uI0:()[],---, +8:u02:(P2), +11:u08:Vanilla, +9:u00:asses, +12:u03:prompts., +8:u10:(p2), +8:u01:(P2), +14:u07:Midjourney, +12:u02:prompts., +8:u00:(P2), +14:u06:Midjourney, +11:u07:Vanilla, +12:u01:prompts., +14:u14:midjourney, +14:u05:Midjourney, +11:u06:Vanilla, +12:u00:prompts., +14:u13:midjourney, +11:u14:vanilla, +14:u04:Midjourney, +11:u05:Vanilla, +14:u12:midjourney, +11:u13:vanilla, +8:u23:Midj, +14:u03:Midjourney, +11:u04:Vanilla, +14:u11:midjourney, +11:u12:vanilla, +8:u23:Vani, +14:u02:Midjourney, +11:u03:Vanilla, +14:u10:midjourney, +11:u11:vanilla, 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+13:u05:Artifacts, +15:u00:Midjourney,, +13:u04:Artifacts, +13:u03:Artifacts, +13:u02:Artifacts, +13:u01:Artifacts, +13:u00:Artifacts, +15:u08:Imagination, +15:u07:Imagination, +15:u06:Imagination, +15:u14:imagination, +15:u05:Imagination, +16:u08:Fine-grained, +15:u13:imagination, +15:u04:Imagination, +10:u08:Detail, +15:u12:imagination, +15:u03:Imagination, +16:u07:Fine-grained, +9:u08:Style, +10:u07:Detail, +15:u11:imagination, +15:u02:Imagination, +16:u06:Fine-grained, +10:u06:Detail, +15:u10:imagination, +15:u01:Imagination, +16:u05:Fine-grained, +9:u07:Style, +10:u05:Detail, +15:u00:Imagination, +16:u04:Fine-grained, +9:u06:Style, +10:u04:Detail, +16:u03:Fine-grained, +9:u05:Style, +10:u03:Detail, +16:u02:Fine-grained, +9:u04:Style, +10:u02:Detail, +16:u01:Fine-grained, +9:u03:Style, +10:u01:Detail, +16:u00:Fine-grained, +9:u02:Style, +10:u00:Detail, +9:u01:Style, +9:u00:Style, +15:u08:evaluators., +15:u07:evaluators., +12:u08:FID-[12], +15:u06:evaluators., +15:u05:evaluators., +13:uI2:.[],-.-.,, +12:u07:FID-[12], +15:u04:evaluators., +13:uI1:.[],-.-.,, +12:u06:FID-[12], +15:u03:evaluators., +12:u14:fid-[12], +13:uI0:.[],-.-.,, +12:u05:FID-[12], +15:u02:evaluators., +12:u13:fid-[12], +15:uI2:-[]-[,]-,--, +12:u04:FID-[12], +15:u01:evaluators., +12:u12:fid-[12], +15:uI1:-[]-[,]-,--, +12:u03:FID-[12], +15:u00:evaluators., +12:u11:fid-[12], +15:uI0:-[]-[,]-,--, +11:uI2:[,,,],,, +12:u02:FID-[12], +12:u10:fid-[12], +11:uI1:[,,,],,, +12:u01:FID-[12], +15:u08:FID-vs-CLIP, +11:uI0:[,,,],,, +12:u00:FID-[12], +15:u07:FID-vs-CLIP, +15:u06:FID-vs-CLIP, +13:u08:versions., +15:u14:fid-vs-clip, +15:u05:FID-vs-CLIP, +15:u08:Contrarily,, +15:u13:fid-vs-clip, +11:uI2:--.-[]., +15:u04:FID-vs-CLIP, +13:u07:versions., +15:u07:Contrarily,, +15:u12:fid-vs-clip, +11:uI1:--.-[]., +15:u03:FID-vs-CLIP, +13:u06:versions., +15:u06:Contrarily,, +15:u11:fid-vs-clip, +13:u14:versions., +11:uI0:--.-[]., +15:u02:FID-vs-CLIP, +13:u05:versions., +7:u08:10k, +15:u05:Contrarily,, +15:u10:fid-vs-clip, +13:u13:versions., +15:u01:FID-vs-CLIP, +13:u04:versions., +15:u04:Contrarily,, +13:u12:versions., +15:u00:FID-vs-CLIP, +13:u03:versions., +7:u07:10k, +15:u03:Contrarily,, +13:u11:versions., +13:u02:versions., +7:u06:10k, +15:u02:Contrarily,, +13:u10:versions., +7:u14:10k, +13:u01:versions., +7:u05:10k, +15:u01:Contrarily,, +7:u13:10k, +13:u00:versions., +7:u04:10k, +15:u00:Contrarily,, +9:u08:(top), +7:u12:10k, +7:u22:10k, +7:u23:10k, +7:u03:10k, +9:u08:shot,, +9:u07:(top), +10:u08:focus,, +7:u11:10k, +7:u02:10k, +9:u06:(top), +10:u07:focus,, +8:u08:8k"., +7:u10:10k, +11:u14:prompt:, +13:uI2::(-)()()., +7:u01:10k, +9:u07:shot,, +9:u05:(top), +10:u06:focus,, +8:u07:8k"., +11:u13:prompt:, +13:uI1::(-)()()., +12:uI2::()",,,,, +7:u00:10k, +9:u06:shot,, +12:u08:'Vibrant, +9:u04:(top), +10:u05:focus,, +8:u06:8k"., +11:u12:prompt:, +9:u14:shot,, +13:uI0::(-)()()., +12:uI1::()",,,,, +10:uI2:,"()",, +9:u05:shot,, +9:u03:(top), +10:u04:focus,, +8:u05:8k"., +11:u11:prompt:, +9:u13:shot,, +12:uI0::()",,,,, +10:uI1:,"()",, +9:uI2:,".-., +9:u04:shot,, +12:u07:'Vibrant, +9:u02:(top), +10:u03:focus,, +8:u04:8k"., +11:u10:prompt:, +9:u12:shot,, +8:u23:shot, +10:uI0:,"()",, +9:uI1:,".-., +9:u03:shot,, +12:u06:'Vibrant, +11:u08:sitting, +9:u01:(top), +10:u02:focus,, +8:u03:8k"., +9:u11:shot,, +12:u14:'vibrant, +9:uI0:,".-., +9:u02:shot,, +12:u05:'Vibrant, +9:u00:(top), +10:u01:focus,, +8:u02:8k"., +9:u10:shot,, +12:u13:'vibrant, +9:u01:shot,, +12:u04:'Vibrant, +11:u07:sitting, +10:u00:focus,, +8:u01:8k"., +12:u12:'vibrant, +7:u22:'Vi, +8:u23:'Vib, +9:u00:shot,, +12:u03:'Vibrant, +11:u06:sitting, +8:u00:8k"., +12:u11:'vibrant, +11:u14:sitting, +12:u02:'Vibrant, +11:u05:sitting, +9:u08:'Cute, +12:u10:'vibrant, +11:u13:sitting, +12:u01:'Vibrant, +11:u04:sitting, +8:u08:cozy, +12:u08:adorable, +11:u12:sitting, +8:u23:sitt, +12:u00:'Vibrant, +11:u03:sitting, +9:u07:'Cute, +12:u07:adorable, +11:u11:sitting, +11:u02:sitting, +9:u06:'Cute, +8:u07:cozy, +12:u06:adorable, +11:u10:sitting, +9:u14:'cute, +11:u01:sitting, +9:u05:'Cute, +8:u06:cozy, +12:u05:adorable, +9:u13:'cute, +8:u14:cozy, +11:u00:sitting, +9:u04:'Cute, +8:u05:cozy, +9:u08:Opera, +12:u04:adorable, +9:u12:'cute, +8:u13:cozy, +7:u22:'Cu, +8:u23:'Cut, +9:u03:'Cute, +8:u04:cozy, +12:u03:adorable, +9:u08:House, +9:u11:'cute, +8:u12:cozy, +7:u22:coz, +8:u23:cozy, +9:u02:'Cute, +8:u03:cozy, +9:u07:Opera, +12:u02:adorable, +9:u07:House, +9:u10:'cute, +8:u11:cozy, +9:u01:'Cute, +8:u02:cozy, +9:u06:Opera, +12:u01:adorable, +9:u06:House, +8:u10:cozy, +9:u14:opera, +9:u00:'Cute, +8:u01:cozy, +9:u05:Opera, +12:u00:adorable, +9:u05:House, +9:u13:opera, +9:uI2:""!.', +8:u00:cozy, +9:u04:Opera, +14:u08:Diffusion., +9:u04:House, +9:u12:opera, +9:uI1:""!.', +9:u03:Opera, +9:u03:House, +9:u11:opera, +9:uI0:""!.', +9:u02:Opera, +14:u07:Diffusion., +9:u02:House, +9:u10:opera, +9:u01:Opera, +14:u06:Diffusion., +12:u08:'Monster, +9:u01:House, +9:u00:Opera, +14:u05:Diffusion., +9:u00:House, +14:u04:Diffusion., +12:u07:'Monster, +10:u08:horror, +10:uI2:[]-.[], +14:u03:Diffusion., +12:u06:'Monster, +10:u07:horror, +12:u14:'monster, +10:uI1:[]-.[], +14:u02:Diffusion., +12:u05:'Monster, +10:u06:horror, +12:u13:'monster, +10:uI0:[]-.[], +14:u01:Diffusion., +12:u04:'Monster, +10:u05:horror, +12:u12:'monster, +7:u22:'Mo, +8:u23:'Mon, +14:u00:Diffusion., +12:u03:'Monster, +10:u04:horror, +12:u11:'monster, +12:u02:'Monster, +10:u03:horror, +12:u10:'monster, +12:u01:'Monster, +10:u02:horror, +12:u00:'Monster, +10:u01:horror, +10:u00:horror, +8:u08:1920, +8:u14:1984, +8:u13:1984, +8:u07:1920, +8:u12:1984, +8:u06:1920, +8:u08:1856, +8:u11:1984, +8:u14:1920, +8:u05:1920, +8:u10:1984, +8:u13:1920, +8:u04:1920, +8:u07:1856, +8:u12:1920, +8:u03:1920, +8:u06:1856, +8:u11:1920, +8:u14:1856, +8:u02:1920, +8:u05:1856, +8:u10:1920, +8:u13:1856, +8:u01:1920, +8:u04:1856, +8:u12:1856, +8:u23:1856, +8:u00:1920, +8:u03:1856, +8:u08:1728, +8:u11:1856, +8:u02:1856, +8:u10:1856, +8:u01:1856, +8:u07:1728, +8:u00:1856, +8:u06:1728, +8:u08:1664, +8:u14:1728, +8:u05:1728, +8:u13:1728, +8:u04:1728, +8:u07:1664, +8:u12:1728, +8:u23:1728, +8:u03:1728, +8:u06:1664, +8:u11:1728, +8:u14:1664, +8:u02:1728, +8:u05:1664, +8:u10:1728, +8:u13:1664, +8:u01:1728, +8:u04:1664, +8:u12:1664, +8:u00:1728, +8:u03:1664, +8:u11:1664, +8:u02:1664, +8:u10:1664, +8:u01:1664, +8:u00:1664, +8:u08:1344, +8:u07:1344, +8:u06:1344, +8:u14:1344, +8:u05:1344, +8:u13:1344, +8:u04:1344, +8:u12:1344, +8:u23:1344, +8:u03:1344, +8:u11:1344, +8:u02:1344, +8:u10:1344, +8:u01:1344, +8:u00:1344, +8:u08:1216, +8:u07:1216, +8:u06:1216, +8:u08:1152, +8:u14:1216, +8:u05:1216, +8:u13:1216, +8:u04:1216, +8:u07:1152, +8:u12:1216, +8:u03:1216, +8:u06:1152, +8:u11:1216, +8:u14:1152, +8:u02:1216, +8:u05:1152, +8:u10:1216, +8:u13:1152, +8:u01:1216, +8:u04:1152, +8:u12:1152, +7:u14:896, +8:u00:1216, +8:u03:1152, +8:u11:1152, +7:u13:896, +8:u02:1152, +8:u10:1152, +7:u12:896, +7:u22:896, +7:u23:896, +8:u01:1152, +7:u11:896, +8:u00:1152, +7:u10:896, +8:u08:2.89, +8:u07:2.89, +8:u06:2.89, +8:u14:2.89, +8:u05:2.89, +8:u13:2.89, +8:u04:2.89, +8:u12:2.89, +8:u23:2.89, +8:u03:2.89, +8:u11:2.89, +8:u02:2.89, +8:u10:2.89, +8:u01:2.89, +8:u00:2.89, +8:u08:3.88, +8:u07:3.88, +8:u06:3.88, +8:u14:3.88, +8:u05:3.88, +8:u13:3.88, +8:u04:3.88, +8:u12:3.88, +8:u23:3.88, +8:u03:3.88, +15:u08:Pseudo-code, +8:u11:3.88, +8:u02:3.88, +15:u07:Pseudo-code, +8:u10:3.88, +8:u01:3.88, +15:u06:Pseudo-code, +8:u00:3.88, +15:u05:Pseudo-code, +15:u04:Pseudo-code, +14:u08:batch_size, +15:u03:Pseudo-code, +14:u07:batch_size, +15:u02:Pseudo-code, +14:u06:batch_size, +14:u08:pooled_dim, +15:u01:Pseudo-code, +14:u05:batch_size, +14:u07:pooled_dim, +15:u00:Pseudo-code, +14:u04:batch_size, +14:u06:pooled_dim, +7:u08:def, +7:u08:""", +14:u03:batch_size, +14:u05:pooled_dim, +7:u07:def, +14:u02:batch_size, +14:u04:pooled_dim, +7:u06:def, +7:u07:""", +14:u01:batch_size, +14:u03:pooled_dim, +7:u05:def, +7:u06:""", +14:u00:batch_size, +14:u02:pooled_dim, +7:u04:def, +14:u08:sinusoidal, +7:u14:""", +7:u05:""", +14:u01:pooled_dim, +7:u03:def, +14:u07:sinusoidal, +7:u13:""", +7:u04:""", +14:u00:pooled_dim, +7:u02:def, +14:u06:sinusoidal, +7:u12:""", +7:u23:""", +7:u03:""", +7:u01:def, +14:u05:sinusoidal, +7:u11:""", +7:u02:""", +7:u00:def, +14:u04:sinusoidal, +9:u08:param, +7:u10:""", +7:u01:""", +14:u03:sinusoidal, +9:u07:param, +7:u00:""", +14:u02:sinusoidal, +9:u06:param, +14:u01:sinusoidal, +9:u05:param, +9:uI2:::[,], +14:u00:sinusoidal, +9:u04:param, +9:uI1:::[,], +9:u03:param, +9:uI0:::[,], +9:u02:param, +9:u01:param, +9:u00:param, +11:uI2::.,)-.:, +11:uI1::.,)-.:, +10:u08:assert, +11:uI0::.,)-.:, +10:u07:assert, +10:uI2:[...,], +10:u06:assert, +10:u14:assert, +10:uI1:[...,], +10:u05:assert, +10:u13:assert, +10:uI0:[...,], +10:u04:assert, +10:u12:assert, +10:u03:assert, +10:u11:assert, +10:u02:assert, +11:u08:fourier, +10:u10:assert, +10:u01:assert, +7:u08:emb, +11:u07:fourier, +12:uI2:(,"-()"), +10:u00:assert, +11:u06:fourier, +12:uI1:(,"-()"), +7:u07:emb, +7:u08:d_f, +11:u05:fourier, +12:uI0:(,"-()"), +7:u06:emb, +11:u04:fourier, +7:u14:emb, +7:u05:emb, +7:u07:d_f, +11:u03:fourier, +7:u13:emb, +7:u04:emb, +7:u06:d_f, +11:u02:fourier, +7:u12:emb, +7:u14:d_f, +7:u23:emb, +7:u03:emb, +7:u05:d_f, +11:u01:fourier, +7:u11:emb, +7:u13:d_f, +7:u02:emb, +7:u04:d_f, +11:u00:fourier, +6:u08:=b, +7:u10:emb, +7:u12:d_f, +6:u21:d_, +7:u22:d_f, +7:u23:d_f, +7:u01:emb, +7:u03:d_f, +6:u07:=b, +7:u11:d_f, +14:uI2:(,"()-()",, +7:u00:emb, +7:u02:d_f, +6:u06:=b, +7:u10:d_f, +14:uI1:(,"()-()",, +7:u01:d_f, +6:u05:=b, +14:uI0:(,"()-()",, +7:u00:d_f, +6:u04:=b, +6:u03:=b, +6:u02:=b, +10:u08:c_size, +6:u01:=b, +6:u00:=b, +10:u07:c_size, +10:u08:c_crop, +8:uI2:#..., +10:u06:c_size, +10:u14:c_size, +8:uI1:#..., +10:u05:c_size, +10:u07:c_crop, +10:u13:c_size, +8:uI0:#..., +10:u04:c_size, +10:u06:c_crop, +10:u12:c_size, +10:u14:c_crop, +6:u21:c_, +7:u22:c_s, +8:u23:c_si, +10:u03:c_size, +10:u05:c_crop, +8:u08:c_ar, +10:u11:c_size, +10:u13:c_crop, +10:u02:c_size, +10:u04:c_crop, +10:u10:c_size, +10:u12:c_crop, +7:u22:c_c, +8:u23:c_cr, +10:u01:c_size, +10:u03:c_crop, +8:u07:c_ar, +10:u11:c_crop, +10:u00:c_size, +10:u02:c_crop, +8:u06:c_ar, +10:u10:c_crop, +8:u14:c_ar, +10:u01:c_crop, +8:u05:c_ar, +16:u08:c_pooled_txt, +8:u13:c_ar, +10:u00:c_crop, +8:u04:c_ar, +8:u12:c_ar, +7:u22:c_a, +8:u23:c_ar, +8:u03:c_ar, +16:u07:c_pooled_txt, +8:u11:c_ar, +8:u02:c_ar, +16:u06:c_pooled_txt, +8:u10:c_ar, +16:u14:c_pooled_txt, +8:u01:c_ar, +16:u05:c_pooled_txt, +14:u08:c_size_emb, +16:u13:c_pooled_txt, +8:u00:c_ar, +16:u04:c_pooled_txt, +16:u12:c_pooled_txt, +7:u22:c_p, +8:u23:c_po, +16:u03:c_pooled_txt, +14:u07:c_size_emb, +16:u11:c_pooled_txt, +16:u02:c_pooled_txt, +14:u06:c_size_emb, +16:u10:c_pooled_txt, +14:u14:c_size_emb, +16:u01:c_pooled_txt, +14:u05:c_size_emb, +14:u08:c_crop_emb, +14:u13:c_size_emb, +16:u00:c_pooled_txt, +14:u04:c_size_emb, +14:u12:c_size_emb, +14:u03:c_size_emb, +14:u07:c_crop_emb, +14:u11:c_size_emb, 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+10:u04:Zeming, +11:u05:DeVito,, +11:u06:Soumith, +8:u08:Alec, +58:u10:novelai-improvements-on-stable-diffusion-e10d38db82ac., +12:u12:killeen,, +58:u01:novelai-improvements-on-stable-diffusion-e10d38db82ac., +12:u03:Killeen,, +16:u08:Transferable, +12:u00:NovelAI., +10:u03:Zeming, +11:u04:DeVito,, +11:u05:Soumith, +8:u07:Alec, +12:u11:killeen,, +58:u00:novelai-improvements-on-stable-diffusion-e10d38db82ac., +12:u02:Killeen,, +11:u07:Sastry,, +10:u02:Zeming, +11:u03:DeVito,, +11:u04:Soumith, +8:u06:Alec, +12:u10:killeen,, +12:uI2:[]..:.,., +12:u01:Killeen,, +11:u06:Sastry,, +16:u07:Transferable, +10:u01:Zeming, +11:u02:DeVito,, +11:u03:Soumith, +8:u05:Alec, +10:u08:Aditya, +11:u14:sastry,, +12:uI1:[]..:.,., +12:u00:Killeen,, +11:u05:Sastry,, +16:u06:Transferable, +10:u00:Zeming, +11:u01:DeVito,, +11:u02:Soumith, +8:u04:Alec, +10:u07:Aditya, +11:u13:sastry,, +16:u14:transferable, +12:uI0:[]..:.,., +11:u04:Sastry,, +16:u05:Transferable, +8:u08:Ilya, +11:u00:DeVito,, +11:u01:Soumith, +8:u03:Alec, +10:u06:Aditya, +11:u12:sastry,, +16:u13:transferable, +8:u23:Sast, +11:u03:Sastry,, +16:u04:Transferable, +11:u00:Soumith, +8:u02:Alec, +10:u05:Aditya, +14:u08:Sutskever., +11:u11:sastry,, +16:u12:transferable, +20:uI2:[].•,.://.///., +11:u02:Sastry,, +16:u03:Transferable, +8:u07:Ilya, +8:u01:Alec, +10:u04:Aditya, +14:u07:Sutskever., +11:u10:sastry,, +16:u11:transferable, +20:uI1:[].•,.://.///., +11:u01:Sastry,, +16:u02:Transferable, +8:u06:Ilya, +8:u00:Alec, +10:u03:Aditya, +14:u06:Sutskever., +16:u10:transferable, +8:u14:ilya, +20:uI0:[].•,.://.///., +11:u00:Sastry,, +16:u01:Transferable, +8:u05:Ilya, +10:u02:Aditya, +14:u05:Sutskever., +8:u13:ilya, +10:uI2:.---,., +16:u00:Transferable, +8:u04:Ilya, +10:u01:Aditya, +14:u04:Sutskever., +8:u12:ilya, +7:u22:Ily, +8:u23:Ilya, +10:uI1:.---,., +8:u03:Ilya, +10:u00:Aditya, +14:u03:Sutskever., +8:u08:Olaf, +8:u11:ilya, +10:uI0:.---,., +8:u02:Ilya, +14:u02:Sutskever., +8:u07:Olaf, +17:u08:Segmentation., +8:u10:ilya, +8:u01:Ilya, +9:u08:Seyed, +14:u01:Sutskever., +8:u06:Olaf, +17:u07:Segmentation., +11:u08:Chitwan, +8:u00:Ilya, +14:u00:Sutskever., +8:u05:Olaf, +17:u06:Segmentation., +11:u07:Chitwan, +16:u08:Ghasemipour,, +9:u07:Seyed, +8:u04:Olaf, +17:u05:Segmentation., +11:u06:Chitwan, +16:u07:Ghasemipour,, +9:u06:Seyed, +8:u03:Olaf, +17:u04:Segmentation., +11:u05:Chitwan, +16:u06:Ghasemipour,, +9:u14:seyed, +9:u05:Seyed, +8:u02:Olaf, +17:u03:Segmentation., +11:u04:Chitwan, +16:u05:Ghasemipour,, +9:u13:seyed, +7:u14:ho,, +9:u04:Seyed, +8:u01:Olaf, +17:u02:Segmentation., +11:u03:Chitwan, +16:u04:Ghasemipour,, +21:u08:arXiv:2202.00512,, +9:u12:seyed, +7:u13:ho,, +7:u22:Sey, +8:u23:Seye, +9:u03:Seyed, +8:u00:Olaf, +17:u01:Segmentation., +11:u02:Chitwan, +16:u03:Ghasemipour,, +21:u07:arXiv:2202.00512,, +9:u11:seyed, +7:u12:ho,, +7:u22:Ho,, +7:u23:Ho,, +9:u02:Seyed, +17:u00:Segmentation., +11:u01:Chitwan, +16:u02:Ghasemipour,, +21:u06:arXiv:2202.00512,, +9:u10:seyed, +7:u11:ho,, +9:u01:Seyed, +11:u00:Chitwan, +16:u01:Ghasemipour,, +21:u05:arXiv:2202.00512,, +10:u08:Sitian, +7:u10:ho,, +9:u00:Seyed, +16:u00:Ghasemipour,, +21:u04:arXiv:2202.00512,, +10:u07:Sitian, +8:u08:Oron, +21:u03:arXiv:2202.00512,, +10:u06:Sitian, +9:u08:Uriel, +21:u02:arXiv:2202.00512,, +10:u05:Sitian, +9:u07:Uriel, +11:u08:Ashual,, +12:uI2:[],,,,.:, +8:u07:Oron, +21:u01:arXiv:2202.00512,, +10:u04:Sitian, +9:u06:Uriel, +11:u07:Ashual,, +12:uI1:[],,,,.:, +8:u06:Oron, +21:u00:arXiv:2202.00512,, +10:u03:Sitian, +9:u05:Uriel, +11:u06:Ashual,, +10:u08:Jascha, +8:u14:oron, +12:uI0:[],,,,.:, +8:u05:Oron, +10:u02:Sitian, +9:u04:Uriel, +11:u05:Ashual,, +10:u07:Jascha, +8:u13:oron, +14:uI2:,,,,.--:--, +8:u04:Oron, +10:u01:Sitian, +9:u03:Uriel, +11:u04:Ashual,, +10:u06:Jascha, +8:u12:oron, +8:u23:Oron, +14:uI1:,,,,.--:--, +8:u03:Oron, +10:u00:Sitian, +9:u02:Uriel, +11:u03:Ashual,, +10:u05:Jascha, +11:u08:Jiaming, +8:u11:oron, +14:uI0:,,,,.--:--, +8:u02:Oron, +9:u01:Uriel, +11:u02:Ashual,, +10:u04:Jascha, +11:u07:Jiaming, 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+9:u05:Lvmin, +21:u14:arxiv:2302.05543,, +10:uI0:,,.---, +21:u05:arXiv:2302.05543,, +10:u00:Jiahui, +9:u04:Lvmin, +21:u13:arxiv:2302.05543,, +21:u04:arXiv:2302.05543,, +9:u03:Lvmin, +21:u12:arxiv:2302.05543,, +12:uI2:[],,.,,., +21:u03:arXiv:2302.05543,, +9:u02:Lvmin, +21:u11:arxiv:2302.05543,, +12:uI1:[],,.,,., +21:u02:arXiv:2302.05543,, +9:u01:Lvmin, +21:u10:arxiv:2302.05543,, +12:uI0:[],,.,,., +21:u01:arXiv:2302.05543,, +9:u00:Lvmin, 21:u04:arXiv:0705.4500v1, 21:u12:arxiv:0705.4500v1, 21:u03:arXiv:0705.4500v1, @@ -1588003,21 +1591822,12 @@ 7:u07:ECT, 9:uI0:,(;)-, 7:u06:ECT, -11:u08:pixels,, 7:u05:ECT, -11:u07:pixels,, 7:u04:ECT, -11:u06:pixels,, 7:u03:ECT, -11:u05:pixels,, 7:u02:ECT, -11:u04:pixels,, 7:u01:ECT, -11:u03:pixels,, 7:u00:ECT, -11:u02:pixels,, -11:u01:pixels,, -11:u00:pixels,, 7:u08:J(Y, 7:u07:J(Y, 9:u08:lnf(Y, @@ -1593057,7 +1596867,6 @@ 17:u10:o-shp53,sk,ul, 9:u11:retro, 14:u12:edom-ipscs, -7:u22:Edo, 8:u23:Edom, 12:u00:Episomal, 17:u01:O-shp53,SK,UL, @@ -1594851,7 +1598660,6 @@ 6:u04:x), 17:u08:*Relationship, 6:u12:x), -6:u21:x), 6:u22:x), 6:u23:x), 6:u03:x), @@ -1599451,39 +1603259,24 @@ 10:u05:0,5439, 10:u13:0,5439, 10:u04:0,5439, -8:u08:1344, 10:u12:0,5439, 10:u03:0,5439, 10:u11:0,5439, 10:u02:0,5439, -8:u07:1344, 8:u08:2636, 10:u10:0,5439, 10:u01:0,5439, -8:u06:1344, -8:u14:1344, 10:u00:0,5439, -8:u05:1344, 8:u07:2636, -8:u13:1344, -8:u04:1344, 8:u06:2636, -8:u12:1344, 8:u14:2636, -8:u23:1344, -8:u03:1344, 8:u05:2636, -8:u11:1344, 8:u13:2636, -8:u02:1344, 8:u04:2636, -8:u10:1344, 8:u12:2636, 8:u23:2636, -8:u01:1344, 8:u03:2636, 8:u11:2636, -8:u00:1344, 8:u02:2636, 10:u08:0,1603, 8:u10:2636, @@ -1610504,7 +1614297,6 @@ 10:u06:(WldO), 22:u05:Wissenschaftliches, 10:u07:Merkel, -15:u08:deployment., 27:u11:icd-10-diagnosekapiteln, 38:u13:ausgewähltenbehandlungsanlässen., 10:u14:(wldo), @@ -1610515,7 +1614307,6 @@ 10:u05:(WldO), 22:u04:Wissenschaftliches, 10:u06:Merkel, -15:u07:deployment., 27:u10:icd-10-diagnosekapiteln, 38:u12:ausgewähltenbehandlungsanlässen., 10:u13:(wldo), @@ -1610527,7 +1614318,6 @@ 71:u08:content/download/9006/66227/version/1/file/v21-KHEntgG_A-2020_2019_, 22:u03:Wissenschaftliches, 10:u05:Merkel, -15:u06:deployment., 38:u11:ausgewähltenbehandlungsanlässen., 10:u12:(wldo), 7:u22:(Wl, @@ -1610538,7 +1614328,6 @@ 18:u08:Endfassung.pdf, 22:u02:Wissenschaftliches, 10:u04:Merkel, -15:u05:deployment., 38:u10:ausgewähltenbehandlungsanlässen., 10:u11:(wldo), 38:u01:ausgewähltenBehandlungsanlässen., @@ -1610546,7 +1614335,6 @@ 71:u07:content/download/9006/66227/version/1/file/v21-KHEntgG_A-2020_2019_, 22:u01:Wissenschaftliches, 10:u03:Merkel, -15:u04:deployment., 10:u10:(wldo), 38:u00:ausgewähltenBehandlungsanlässen., 10:u01:(WldO), @@ -1610554,7 +1614342,6 @@ 18:u07:Endfassung.pdf, 22:u00:Wissenschaftliches, 10:u02:Merkel, -15:u03:deployment., 71:u14:content/download/9006/66227/version/1/file/v21-khentgg_a-2020_2019_, 16:uI2:.().:://.-./, 10:u00:(WldO), @@ -1610562,7 +1614349,6 @@ 18:u06:Endfassung.pdf, 17:u08:package=shiny, 10:u01:Merkel, -15:u02:deployment., 71:u13:content/download/9006/66227/version/1/file/v21-khentgg_a-2020_2019_, 18:u14:endfassung.pdf, 16:uI1:.().:://.-./, @@ -1610570,7 +1614356,6 @@ 71:u04:content/download/9006/66227/version/1/file/v21-KHEntgG_A-2020_2019_, 18:u05:Endfassung.pdf, 10:u00:Merkel, -15:u01:deployment., 71:u12:content/download/9006/66227/version/1/file/v21-khentgg_a-2020_2019_, 18:u13:endfassung.pdf, 16:uI0:.().:://.-./, @@ -1610579,7 +1614364,6 @@ 18:u04:Endfassung.pdf, 17:u07:package=shiny, 11:u08:Vienna:, -15:u00:deployment., 71:u11:content/download/9006/66227/version/1/file/v21-khentgg_a-2020_2019_, 18:u12:endfassung.pdf, 8:u23:Endf, @@ -1616010,31 +1619794,22 @@ 12:u11:lamented, 17:u01:substitution), 12:u02:lamented, -16:u08:Conditioning, 12:u10:lamented, 17:u00:substitution), 12:u01:lamented, 12:u00:lamented, -16:u07:Conditioning, 13:u08:Isolating, -16:u06:Conditioning, 13:u07:Isolating, -16:u05:Conditioning, 13:u06:Isolating, 19:u08:food-predicting, -16:u04:Conditioning, 13:u05:Isolating, 19:u07:food-predicting, -16:u03:Conditioning, 13:u04:Isolating, 19:u06:food-predicting, -16:u02:Conditioning, 13:u03:Isolating, 19:u05:food-predicting, -16:u01:Conditioning, 13:u02:Isolating, 19:u04:food-predicting, -16:u00:Conditioning, 13:u01:Isolating, 19:u03:food-predicting, 13:u00:Isolating, @@ -1616346,7 +1620121,6 @@ 19:u11:contemporaries,, 19:u02:contemporaries,, 9:u06:date), -17:u08:conditioning., 8:u07:far., 19:u10:contemporaries,, 9:u14:date), @@ -1616356,43 +1620130,30 @@ 9:u13:date), 19:u00:contemporaries,, 9:u04:date), -17:u07:conditioning., 26:u08:efficiency/flexibility, 8:u05:far., 9:u12:date), 9:u03:date), -17:u06:conditioning., 8:u04:far., 9:u11:date), -17:u14:conditioning., 9:u02:date), -17:u05:conditioning., 26:u07:efficiency/flexibility, 8:u03:far., 9:u10:date), -17:u13:conditioning., 9:u01:date), -17:u04:conditioning., 26:u06:efficiency/flexibility, 8:u02:far., -17:u12:conditioning., 26:u14:efficiency/flexibility, 9:u00:date), -17:u03:conditioning., 26:u05:efficiency/flexibility, 8:u01:far., -17:u11:conditioning., 26:u13:efficiency/flexibility, -17:u02:conditioning., 26:u04:efficiency/flexibility, 8:u00:far., -17:u10:conditioning., 26:u12:efficiency/flexibility, -17:u01:conditioning., 26:u03:efficiency/flexibility, 10:u08:'pure', 26:u11:efficiency/flexibility, -17:u00:conditioning., 26:u02:efficiency/flexibility, 26:u10:efficiency/flexibility, 26:u01:efficiency/flexibility, @@ -1617423,7 +1621184,6 @@ 11:u06:Neural., 17:u13:melanogaster:, 13:uI1:,.,',.()., -11:uI2::......, 17:u04:melanogaster:, 15:u06:Heisenberg,, 11:u00:Ganglia, @@ -1617432,14 +1621192,12 @@ 17:u12:melanogaster:, 15:u14:heisenberg,, 13:uI0:,.,',.()., -11:uI1::......, 17:u03:melanogaster:, 15:u05:Heisenberg,, 15:u01:Neuroethol., 11:u04:Neural., 17:u11:melanogaster:, 15:u13:heisenberg,, -11:uI0::......, 17:u02:melanogaster:, 15:u04:Heisenberg,, 15:u00:Neuroethol., @@ -1631896,16 +1635654,7 @@ 17:u03:Pre-operative, 17:u02:Pre-operative, 17:u01:Pre-operative, -10:u08:gloves, 17:u00:Pre-operative, -10:u07:gloves, -10:u06:gloves, -10:u05:gloves, -10:u04:gloves, -10:u03:gloves, -10:u02:gloves, -10:u01:gloves, -10:u00:gloves, 10:u08:staff., 10:u07:staff., 18:u08:Peri-operative, @@ -1649231,7 +1652980,6 @@ 18:u01:Constructs-The, 6:u10:1r, 15:u12:v5-his-topo, -6:u21:v5, 7:u22:v5-, 8:u23:v5-H, 6:u01:1R, @@ -1681171,59 +1684919,45 @@ 9:u08:SRC1,, 10:u01:Assert, 10:u07:ASSERT, -10:u08:assert, 15:u14:dest1,dest2, 15:u05:DEST1,DEST2, 10:u00:Assert, 10:u06:ASSERT, -10:u07:assert, 15:u13:dest1,dest2, 15:u04:DEST1,DEST2, 9:u07:SRC1,, 10:u05:ASSERT, -10:u06:assert, 15:u12:dest1,dest2, 8:u23:DEST, 15:u03:DEST1,DEST2, 9:u06:SRC1,, 10:u04:ASSERT, -10:u05:assert, 9:u08:DEST1, 15:u11:dest1,dest2, 9:u14:src1,, 15:u02:DEST1,DEST2, 9:u05:SRC1,, 10:u03:ASSERT, -10:u04:assert, 9:u07:DEST1, 15:u10:dest1,dest2, 9:u13:src1,, -10:u14:assert, 15:u01:DEST1,DEST2, 9:u04:SRC1,, 10:u02:ASSERT, -10:u03:assert, 9:u06:DEST1, 9:u12:src1,, -10:u13:assert, 8:u23:SRC1, 15:u00:DEST1,DEST2, 9:u03:SRC1,, 10:u01:ASSERT, -10:u02:assert, 9:u05:DEST1, 9:u11:src1,, -10:u12:assert, 9:u02:SRC1,, 10:u00:ASSERT, -10:u01:assert, 9:u04:DEST1, 9:u10:src1,, -10:u11:assert, 9:u01:SRC1,, -10:u00:assert, 9:u03:DEST1, -10:u10:assert, 9:u00:SRC1,, 11:u08:writes., 9:u02:DEST1, @@ -1682763,24 +1686497,10 @@ 11:u05:La-123., 7:u00:La., 11:u04:La-123., -13:u08:converged, 11:u03:La-123., 11:u02:La-123., -13:u07:converged, 11:u01:La-123., -13:u06:converged, 11:u00:La-123., -13:u14:converged, -13:u05:converged, -13:u13:converged, -13:u04:converged, -13:u12:converged, -13:u03:converged, -13:u11:converged, -13:u02:converged, -13:u10:converged, -13:u01:converged, -13:u00:converged, 10:u08:Fig.2., 10:u07:Fig.2., 10:u06:Fig.2., @@ -1683303,7 +1687023,6 @@ 11:u10:11.7235, 10:u12:3.8824, 11:u13:11.6698, -8:u23:3.88, 10:u00:3.8988, 11:u01:11.7235, 10:u03:3.8824, @@ -1690647,16 +1694366,13 @@ 21:u07:straightforwardly, 21:u06:straightforwardly, 21:u14:straightforwardly, -10:uI2:-[][],, 21:u05:straightforwardly, 13:u08:GeV-scale, 21:u13:straightforwardly, -10:uI1:-[][],, 21:u04:straightforwardly, 13:u07:GeV-scale, 18:u08:multikilohertz, 21:u12:straightforwardly, -10:uI0:-[][],, 21:u03:straightforwardly, 13:u06:GeV-scale, 18:u07:multikilohertz, @@ -1692072,11 +1695788,8 @@ 14:u07:editorials, 14:u06:editorials, 14:u05:editorials, -9:uI2:[,,,], 14:u04:editorials, -9:uI1:[,,,], 14:u03:editorials, -9:uI0:[,,,], 15:u08:[11,12,40]., 14:u02:editorials, 14:u01:editorials, @@ -1698511,7 +1702224,6 @@ 11:u00:Gauldin, 25:u01:Healthcare-associated, 13:u05:Blanchard, -9:u08:2022., 13:u13:blanchard, 13:uI2:,,,...,-., 25:u00:Healthcare-associated, @@ -1698519,26 +1702231,13 @@ 13:u12:blanchard, 13:uI1:,,,...,-., 13:u03:Blanchard, -9:u07:2022., 13:u11:blanchard, 13:uI0:,,,...,-., 13:u02:Blanchard, -9:u06:2022., 13:u10:blanchard, -9:u14:2022., 13:u01:Blanchard, -9:u05:2022., -9:u13:2022., 13:u00:Blanchard, -9:u04:2022., -9:u12:2022., -9:u03:2022., -9:u11:2022., -9:u02:2022., -9:u10:2022., -9:u01:2022., 11:u08:07810-8, -9:u00:2022., 11:u07:07810-8, 9:u08:Sturm, 11:u06:07810-8, @@ -1701726,7 +1705425,6 @@ 10:u08:Boutry, 14:u12:dusterhoft, 13:u14:obermaier, -8:u23:Dust, 14:u03:Dusterhoft, 13:u05:Obermaier, 12:u08:Schueren, @@ -1720870,7 +1724568,6 @@ 7:u07:Sa:, 10:u08:90:10), 12:u03:céphame, -8:u08:1728, 16:u11:pyrazolino-1, 12:u12:anhydre., 16:u02:pyrazolino-1, @@ -1720879,7 +1724576,6 @@ 13:u07:lactame),, 8:u08:5,84, 12:u02:céphame, -8:u07:1728, 16:u10:pyrazolino-1, 12:u11:anhydre., 7:u14:sa:, @@ -1720889,7 +1724585,6 @@ 13:u06:lactame),, 10:u07:90:10), 12:u01:céphame, -8:u06:1728, 12:u10:anhydre., 7:u13:sa:, 13:u14:lactame),, @@ -1720902,7 +1724597,6 @@ 8:u07:5,84, 8:u08:148;, 12:u00:céphame, -8:u05:1728, 7:u12:sa:, 13:u13:lactame),, 10:u14:90:10), @@ -1720916,7 +1724610,6 @@ 10:u05:90:10), 8:u06:5,84, 7:u08:'7=, -8:u04:1728, 7:u11:sa:, 13:u12:lactame),, 10:u13:90:10), @@ -1720929,7 +1724622,6 @@ 10:u04:90:10), 8:u05:5,84, 8:u07:148;, -8:u03:1728, 8:u08:154;, 7:u10:sa:, 13:u11:lactame),, @@ -1720945,7 +1724637,6 @@ 8:u04:5,84, 8:u06:148;, 7:u07:'7=, -8:u02:1728, 8:u07:154;, 8:u08:C8);, 13:u10:lactame),, @@ -1720962,7 +1724653,6 @@ 8:u03:5,84, 8:u05:148;, 7:u06:'7=, -8:u01:1728, 8:u06:154;, 8:u07:C8);, 10:u08:59,74,, @@ -1720979,7 +1724669,6 @@ 8:u04:148;, 7:u05:'7=, 10:u08:tame),, -8:u00:1728, 8:u05:154;, 8:u06:C8);, 10:u07:59,74,, @@ -1724939,7 +1728628,6 @@ 15:u14:(esj.(£."), 15:u05:(ESJ.(£."), 9:u07:^LOGI, -7:u08:2-1, 16:u01:voltamétrie, 11:u02:Sn(IV)., 12:u03:suivante, @@ -1724957,7 +1728645,6 @@ 10:uI1:(.(."), 15:u03:(ESJ.(£."), 9:u05:^LOGI, -7:u07:2-1, 11:u00:Sn(IV)., 12:u01:suivante, 15:u11:(esj.(£."), @@ -1724965,7 +1728652,6 @@ 10:uI0:(.(."), 15:u02:(ESJ.(£."), 9:u04:^LOGI, -7:u06:2-1, 8:u07:[SnF, 12:u00:suivante, 15:u10:(esj.(£."), @@ -1724975,7 +1728661,6 @@ 8:u23:^LOG, 15:u01:(ESJ.(£."), 9:u03:^LOGI, -7:u05:2-1, 8:u06:[SnF, 6:u08:~], 9:u11:^logi, @@ -1724983,7 +1728668,6 @@ 8:u14:[snf, 15:u00:(ESJ.(£."), 9:u02:^LOGI, -7:u04:2-1, 8:u05:[SnF, 6:u07:~], 9:u10:^logi, @@ -1724992,7 +1728676,6 @@ 7:u23:2-1, 10:uI2:["][-], 9:u01:^LOGI, -7:u03:2-1, 8:u04:[SnF, 6:u06:~], 7:u11:2-1, @@ -1725002,7 +1728685,6 @@ 10:uI1:["][-], 8:uI2:-[][, 9:u00:^LOGI, -7:u02:2-1, 8:u03:[SnF, 6:u05:~], 7:u10:2-1, @@ -1725010,13 +1728692,11 @@ 10:uI0:["][-], 8:uI1:-[][, 6:uI2:]', -7:u01:2-1, 8:u02:[SnF, 6:u04:~], 8:u10:[snf, 8:uI0:-[][, 6:uI1:]', -7:u00:2-1, 8:u01:[SnF, 9:u08:0,059, 6:u03:~], @@ -1737888,7 +1741568,6 @@ 16:u02:5-diaza-FMN,, 9:u04:glove, 16:u10:5-diaza-fmn,, -8:u23:glov, 16:u01:5-diaza-FMN,, 9:u03:glove, 16:u00:5-diaza-FMN,, @@ -1752757,39 +1756436,30 @@ 17:u07:(below-left)., 17:u06:(below-left)., 12:u07:browsing, -6:u08:TV, 17:u14:(below-left)., 9:uI2:(-)"", 17:u05:(below-left)., 12:u06:browsing, -6:u07:TV, 17:u13:(below-left)., 9:uI1:(-)"", 17:u04:(below-left)., 12:u05:browsing, -6:u06:TV, 17:u12:(below-left)., 9:uI0:(-)"", 17:u03:(below-left)., 12:u04:browsing, -6:u05:TV, 17:u11:(below-left)., 17:u02:(below-left)., 12:u03:browsing, -6:u04:TV, 17:u10:(below-left)., 12:uI2:(-).,,"", 17:u01:(below-left)., 12:u02:browsing, -6:u03:TV, 12:uI1:(-).,,"", 17:u00:(below-left)., 12:u01:browsing, -6:u02:TV, 12:uI0:(-).,,"", 12:u00:browsing, -6:u01:TV, -6:u00:TV, 8:u08:deck, 8:u07:deck, 11:u14:picking, @@ -1759755,18 +1763425,9 @@ 9:uI2:-,).., 9:uI1:-,).., 9:uI0:-,).., -9:u08:(top), -9:u07:(top), -9:u06:(top), -9:u05:(top), 12:uI2:()().,-,, -9:u04:(top), 12:uI1:()().,-,, -9:u03:(top), 12:uI0:()().,-,, -9:u02:(top), -9:u01:(top), -9:u00:(top), 11:u08:(Newman, 11:u07:(Newman, 10:uI2:()(-)(, @@ -1761227,21 +1764888,16 @@ 16:u08:HutchinsonID, 14:u06:Sawierucha, 16:u07:HutchinsonID, -9:u14:jonas, 14:u05:Sawierucha, 16:u06:HutchinsonID, -9:u13:jonas, 14:u04:Sawierucha, 16:u05:HutchinsonID, -9:u12:jonas, 14:u03:Sawierucha, 16:u04:HutchinsonID, 25:u08:norbert.ahrens@ukr.de, -9:u11:jonas, 14:u02:Sawierucha, 16:u03:HutchinsonID, 25:u07:norbert.ahrens@ukr.de, -9:u10:jonas, 14:u01:Sawierucha, 16:u02:HutchinsonID, 25:u06:norbert.ahrens@ukr.de, @@ -1774318,7 +1777974,6 @@ 17:u07:metagenomics., 17:u04:metagenomics,, 11:u12:shotgun, -8:u23:shot, 17:u06:metagenomics., 17:u03:metagenomics,, 11:u11:shotgun, @@ -1790420,21 +1794075,12 @@ 25:u00:rejected_trajectories, 21:u01:sample.trajectory, 21:u00:sample.trajectory, -7:u08:-we, -7:u07:-we, -7:u06:-we, -7:u05:-we, 17:u08:previous_file, -7:u04:-we, -7:u03:-we, 17:u07:previous_file, -7:u02:-we, 17:u06:previous_file, 7:u08:phi, -7:u01:-we, 17:u14:previous_file, 17:u05:previous_file, -7:u00:-we, 17:u13:previous_file, 13:uI2:.(".",''), 17:u04:previous_file, @@ -1790885,10 +1794531,7 @@ 11:u10:lnp(λ), 11:u01:lnP(λ), 11:u00:lnP(λ), -9:uI2:..,.:, -9:uI1:..,.:, 13:uI2:()(-).:.:, -9:uI0:..,.:, 13:uI1:()(-).:.:, 11:uI2:.()[,]., 16:u08:equil_scheme, @@ -1791672,44 +1795315,35 @@ 14:u01:topology)., 24:u00:toys.Engine(options,, 14:u00:topology)., -7:u08:def, 19:u08:yval(snapshot):, -7:u07:def, 19:u07:yval(snapshot):, 22:u08:snapshot.xyz[0][1], -7:u06:def, 19:u06:yval(snapshot):, 22:u07:snapshot.xyz[0][1], 8:u08:xval, -7:u05:def, 19:u05:yval(snapshot):, 22:u06:snapshot.xyz[0][1], 8:u07:xval, -7:u04:def, 19:u04:yval(snapshot):, 22:u05:snapshot.xyz[0][1], 8:u06:xval, 7:u23:def, -7:u03:def, 19:u03:yval(snapshot):, 22:u04:snapshot.xyz[0][1], 8:u05:xval, 10:uI2:,[][],, -7:u02:def, 11:u08:x_lower, 19:u02:yval(snapshot):, 22:u03:snapshot.xyz[0][1], 8:u04:xval, 19:u08:FunctionCV("x",, 10:uI1:,[][],, -7:u01:def, 18:u08:float("-inf"),, 19:u01:yval(snapshot):, 22:u02:snapshot.xyz[0][1], 8:u03:xval, 19:u07:FunctionCV("x",, 10:uI0:,[][],, -7:u00:def, 11:u07:x_lower, 19:u00:yval(snapshot):, 22:u01:snapshot.xyz[0][1], @@ -1808191,8 +1811825,6 @@ 9:u10:balls, 12:u12:baptista, 12:u14:barhoumi, -7:u22:Bap, -8:u23:Bapt, 8:u00:AZUR, 9:u01:Balls, 12:u03:Baptista, @@ -1811599,7 +1815231,6 @@ 14:u12:211.2±1.1, 13:u13:85.1±1.2, 13:u14:90.0±3.1, -8:u23:211., 14:u00:197.4±1.5, 13:u01:95.7±5.1, 14:u02:106.2±1.4, @@ -1863006,45 +1866637,36 @@ 11:u00:illegal, 13:u01:General's, 7:u03:$24, -6:u08:RJ, 13:u12:payments,, 7:uI0:$,., 9:u07:ucts., 13:u00:General's, 7:u02:$24, -6:u07:RJ, 13:u11:payments,, 9:u06:ucts., 7:u01:$24, -6:u06:RJ, 9:u08:58e72, 13:u10:payments,, 9:u14:ucts., 9:u05:ucts., 7:u00:$24, -6:u05:RJ, 9:u07:58e72, 9:u13:ucts., 9:u04:ucts., -6:u04:RJ, 9:u06:58e72, 9:u12:ucts., 9:u03:ucts., 13:u08:retailers, -6:u03:RJ, 9:u05:58e72, 9:u11:ucts., 9:u02:ucts., -6:u02:RJ, 9:u04:58e72, 9:u10:ucts., 9:u01:ucts., 13:u07:retailers, -6:u01:RJ, 9:u03:58e72, 9:u00:ucts., 13:u06:retailers, -6:u00:RJ, 9:u02:58e72, 13:u14:retailers, 13:u05:retailers, @@ -1863903,21 +1867525,14 @@ 8:u14:21.1, 8:u05:21.1, 8:u13:21.1, -6:u14:rj, 8:u04:21.1, 8:u12:21.1, -6:u13:rj, 8:u03:21.1, 8:u11:21.1, -6:u12:rj, -6:u22:RJ, -6:u23:RJ, 8:u02:21.1, 8:u10:21.1, -6:u11:rj, 8:u01:21.1, 13:u08:Lorillard, -6:u10:rj, 8:u00:21.1, 13:u07:Lorillard, 13:u06:Lorillard, @@ -1864356,16 +1867971,7 @@ 14:u13:marketing,, 14:u12:marketing,, 14:u11:marketing,, -10:u08:local,, 14:u10:marketing,, -10:u07:local,, -10:u06:local,, -10:u05:local,, -10:u04:local,, -10:u03:local,, -10:u02:local,, -10:u01:local,, -10:u00:local,, 9:u08:2002*, 9:u07:2002*, 9:u06:2002*, @@ -1910895,43 +1914501,34 @@ 8:u04:C000, 8:u05:E04A, 8:u06:W033, -13:u08:versions., 8:u02:E00D, 8:u03:C000, 8:u04:E04A, 8:u05:W033, -13:u07:versions., 8:u01:E00D, 8:u02:C000, 8:u03:E04A, 8:u04:W033, -13:u06:versions., 9:uI2::-.,,, 10:u08:tocopy, 8:u00:E00D, 8:u01:C000, 8:u02:E04A, 8:u03:W033, -13:u05:versions., 9:uI1::-.,,, 8:u00:C000, 8:u01:E04A, 8:u02:W033, -13:u04:versions., 9:uI0::-.,,, 10:u07:tocopy, 8:u00:E04A, 8:u01:W033, -13:u03:versions., 10:u06:tocopy, 8:u00:W033, -13:u02:versions., 10:u14:tocopy, 10:u05:tocopy, -13:u01:versions., 10:u13:tocopy, 10:u04:tocopy, -13:u00:versions., 10:u12:tocopy, 10:u03:tocopy, 10:u11:tocopy, @@ -1917847,7 +1921444,6 @@ 24:u13:www.csie.ntu.edu.tw/, 15:u00:EUROSPEECH,, 24:u04:www.csie.ntu.edu.tw/, -8:u08:Eric, 11:u02:LIBSVM:, 11:u08:Edward,, 24:u12:www.csie.ntu.edu.tw/, @@ -1917860,7 +1921456,6 @@ 24:u11:www.csie.ntu.edu.tw/, 24:u02:www.csie.ntu.edu.tw/, 12:u06:Cutrell,, -8:u07:Eric, 13:u08:messaging, 11:u00:LIBSVM:, 11:u06:Edward,, @@ -1917869,7 +1921464,6 @@ 12:u14:cutrell,, 24:u01:www.csie.ntu.edu.tw/, 12:u05:Cutrell,, -8:u06:Eric, 15:u07:disruption,, 11:u05:Edward,, 12:u06:Horvitz., @@ -1917877,7 +1921471,6 @@ 8:u14:eric, 24:u00:www.csie.ntu.edu.tw/, 12:u04:Cutrell,, -8:u05:Eric, 15:u06:disruption,, 13:u07:messaging, 13:u08:INTERACT,, @@ -1917888,7 +1921481,6 @@ 15:u14:disruption,, 8:u23:Cutr, 12:u03:Cutrell,, -8:u04:Eric, 15:u05:disruption,, 13:u06:messaging, 11:u03:Edward,, @@ -1917897,7 +1921489,6 @@ 8:u12:eric, 15:u13:disruption,, 12:u02:Cutrell,, -8:u03:Eric, 15:u04:disruption,, 13:u05:messaging, 13:u07:INTERACT,, @@ -1917907,7 +1921498,6 @@ 8:u11:eric, 15:u12:disruption,, 12:u01:Cutrell,, -8:u02:Eric, 15:u03:disruption,, 13:u04:messaging, 13:u06:INTERACT,, @@ -1917917,7 +1921507,6 @@ 15:u11:disruption,, 13:u14:interact,, 12:u00:Cutrell,, -8:u01:Eric, 15:u02:disruption,, 13:u03:messaging, 13:u05:INTERACT,, @@ -1917926,7 +1921515,6 @@ 12:u01:Horvitz., 15:u10:disruption,, 13:u13:interact,, -8:u00:Eric, 15:u01:disruption,, 13:u02:messaging, 13:u04:INTERACT,, @@ -1920485,32 +1924073,18 @@ 12:u04:FLJ20315, 8:u11:7.72, 8:u02:7.72, -8:u08:3.88, 12:u03:FLJ20315, 8:u10:7.72, 8:u01:7.72, 12:u02:FLJ20315, 8:u00:7.72, -8:u07:3.88, 12:u01:FLJ20315, -8:u06:3.88, 12:u00:FLJ20315, -8:u14:3.88, -8:u05:3.88, 9:u08:HYAL1, -8:u13:3.88, -8:u04:3.88, 9:u07:HYAL1, -8:u12:3.88, -8:u03:3.88, 9:u06:HYAL1, -8:u11:3.88, -8:u02:3.88, 9:u05:HYAL1, -8:u10:3.88, -8:u01:3.88, 9:u04:HYAL1, -8:u00:3.88, 9:u03:HYAL1, 9:u02:HYAL1, 9:u01:HYAL1, @@ -1926773,27 +1930347,18 @@ 10:u00:Klimov, 9:u05:bonus, 12:u07:flexibly, -16:u08:distillation, 9:u04:bonus, 12:u06:flexibly, -16:u07:distillation, 9:u03:bonus, 12:u05:flexibly, -16:u06:distillation, 9:u02:bonus, 12:u04:flexibly, -16:u05:distillation, 9:u01:bonus, 12:u03:flexibly, -16:u04:distillation, 9:u00:bonus, 12:u02:flexibly, -16:u03:distillation, 12:u01:flexibly, -16:u02:distillation, 12:u00:flexibly, -16:u01:distillation, -16:u00:distillation, 15:u08:impractical, 15:u07:impractical, 15:u06:impractical, @@ -1926813,39 +1930378,31 @@ 9:u12:19-21, 9:u11:19-21, 9:u10:19-21, -9:u08:torch, 12:u08:(19-21)., -9:u07:torch, 12:u07:(19-21)., -9:u06:torch, 13:u08:(7,9,18),, 12:u06:(19-21)., 9:u14:torch, -9:u05:torch, 12:u05:(19-21)., 9:u13:torch, 12:uI2:(-).,,,,, -9:u04:torch, 13:u07:(7,9,18),, 12:u04:(19-21)., 9:u12:torch, 8:u23:torc, 12:uI1:(-).,,,,, -9:u03:torch, 13:u06:(7,9,18),, 12:u03:(19-21)., 9:u11:torch, 13:u14:(7,9,18),, 12:uI0:(-).,,,,, 20:uI2:(,,,),(,,,,,,,),, -9:u02:torch, 13:u05:(7,9,18),, 12:u02:(19-21)., 16:u08:Alphabetical, 9:u10:torch, 13:u13:(7,9,18),, 20:uI1:(,,,),(,,,,,,,),, -9:u01:torch, 13:u04:(7,9,18),, 22:u08:arXiv:1810.12894v1, 12:u01:(19-21)., @@ -1926853,7 +1930410,6 @@ 13:u12:(7,9,18),, 8:u23:(7,9, 20:uI0:(,,,),(,,,,,,,),, -9:u00:torch, 13:u03:(7,9,18),, 12:u00:(19-21)., 16:u06:Alphabetical, @@ -1927503,37 +1931059,22 @@ 12:u01:Gravitar, 12:u13:rewards., 12:u04:rewards., -11:u08:Sastry,, 12:u00:Gravitar, 12:u12:rewards., 12:u03:rewards., 12:u11:rewards., 12:u02:rewards., -11:u07:Sastry,, 12:u10:rewards., 12:u01:rewards., -11:u06:Sastry,, -11:u14:sastry,, 12:u00:rewards., -11:u05:Sastry,, 10:u08:apples, -11:u13:sastry,, 16:uI2:,;.,;.,)..(), -11:u04:Sastry,, 10:u07:apples, -11:u12:sastry,, -8:u23:Sast, 16:uI1:,;.,;.,)..(), -11:u03:Sastry,, 10:u06:apples, -11:u11:sastry,, 16:uI0:,;.,;.,)..(), -11:u02:Sastry,, 10:u05:apples, -11:u10:sastry,, -11:u01:Sastry,, 10:u04:apples, -11:u00:Sastry,, 10:u03:apples, 10:u02:apples, 10:u01:apples, @@ -1928106,26 +1931647,21 @@ 9:u06:Burda, 11:uI2:.,).(.,, 14:u07:Vectorized, -16:u14:distillation, 11:uI1:.,).(.,, 12:uI2:;.,)..(), 14:u06:Vectorized, 12:u08:returns., -16:u13:distillation, 14:u14:vectorized, 11:uI0:.,).(.,, 12:uI1:;.,)..(), 14:u05:Vectorized, -16:u12:distillation, 14:u13:vectorized, 12:uI0:;.,)..(), 14:u04:Vectorized, 12:u07:returns., -16:u11:distillation, 14:u12:vectorized, 14:u03:Vectorized, 12:u06:returns., -16:u10:distillation, 14:u11:vectorized, 12:u14:returns., 14:u02:Vectorized, @@ -1928241,19 +1931777,16 @@ 15:u01:count-based, 10:u04:Burda,, 16:u07:q-ensembles., -11:uI2:--.:.,., 12:u00:Unifying, 13:u07:Kyunghyun, 15:u00:count-based, 10:u03:Burda,, 16:u06:q-ensembles., -11:uI1:--.:.,., 13:u06:Kyunghyun, 9:u08:Misha, 10:u02:Burda,, 16:u05:q-ensembles., 13:u14:kyunghyun, -11:uI0:--.:.,., 13:u05:Kyunghyun, 9:u08:itas., 10:u01:Burda,, @@ -1929259,7 +1932792,6 @@ 12:u07:DeTurck,, 13:u12:sainbayar, 10:u14:haoran, -8:u23:Sain, 13:u03:Sainbayar, 10:u05:Haoran, 9:u08:Wang., @@ -1932467,11 +1935999,6 @@ 8:u10:(∼, 8:u01:(∼, 8:u00:(∼, -12:u14:average., -12:u13:average., -12:u12:average., -12:u11:average., -12:u10:average., 15:u08:0110.7+8738, 15:u07:0110.7+8738, 15:u06:0110.7+8738, @@ -1942972,33 +1946499,17 @@ 7:u03:nb., 7:u11:nb., 7:u02:nb., -11:u08:idation, 7:u10:nb., 7:u01:nb., 7:u00:nb., -11:u07:idation, -11:u06:idation, -11:u14:idation, -11:u05:idation, -11:u13:idation, -11:u04:idation, 10:u08:proxy,, -11:u12:idation, -7:u22:ida, -8:u23:idat, -11:u03:idation, 11:u08:staying, -11:u11:idation, -11:u02:idation, 10:u07:proxy,, 11:u08:rebuild, 11:u07:staying, -11:u10:idation, -11:u01:idation, 10:u06:proxy,, 11:u06:staying, 10:u14:proxy,, -11:u00:idation, 10:u05:proxy,, 11:u07:rebuild, 9:u08:4.1.5, @@ -1950523,46 +1954034,37 @@ 15:u04:supervised., 8:u01:RQ5,, 15:u07:'cost-free', -9:u08:set)., 15:u12:supervised., 15:u03:supervised., 10:u07:(train, 8:u00:RQ5,, 15:u06:'cost-free', -9:u07:set)., 15:u11:supervised., 15:u02:supervised., 10:u06:(train, 15:u05:'cost-free', -9:u06:set)., 15:u10:supervised., 10:u14:(train, 15:u01:supervised., 10:u05:(train, 15:u04:'cost-free', -9:u05:set)., 10:u13:(train, 15:u00:supervised., 10:u04:(train, 15:u03:'cost-free', -9:u04:set)., 10:u12:(train, 10:u03:(train, 13:u08:Zero-Shot, 15:u02:'cost-free', -9:u03:set)., 10:u11:(train, 10:u02:(train, 15:u01:'cost-free', -9:u02:set)., 10:u10:(train, 10:u01:(train, 13:u07:Zero-Shot, 15:u00:'cost-free', -9:u01:set)., 10:u00:(train, 13:u06:Zero-Shot, -9:u00:set)., 13:u05:Zero-Shot, 13:u04:Zero-Shot, 13:u03:Zero-Shot, @@ -1985493,7 +1988995,6 @@ 8:u12:8967, 8:u13:1314, 8:u14:6517, -7:u22:896, 8:u23:8967, 8:u00:9354, 8:u03:8967, @@ -1992629,19 +1996130,16 @@ 10:uI1:.,),)-, 7:u06:ule, 12:u07:service,, -12:u08:benefit., 7:u14:ule, 10:uI0:.,),)-, 7:u05:ule, 12:u06:service,, 12:u07:munity's, -12:u07:benefit., 7:u13:ule, 12:u14:service,, 7:u04:ule, 12:u05:service,, 12:u06:munity's, -12:u06:benefit., 7:u12:ule, 12:u13:service,, 12:u14:munity's, @@ -1992649,33 +1996147,27 @@ 7:u03:ule, 12:u04:service,, 12:u05:munity's, -12:u05:benefit., 7:u11:ule, 12:u12:service,, 12:u13:munity's, 7:u02:ule, 12:u03:service,, 12:u04:munity's, -12:u04:benefit., 7:u10:ule, 12:u11:service,, 12:u12:munity's, 7:u01:ule, 12:u02:service,, 12:u03:munity's, -12:u03:benefit., 12:u10:service,, 12:u11:munity's, 7:u00:ule, 12:u01:service,, 12:u02:munity's, -12:u02:benefit., 12:u10:munity's, 12:u00:service,, 12:u01:munity's, -12:u01:benefit., 12:u00:munity's, -12:u00:benefit., 12:u08:toolkit,, 12:u07:toolkit,, 12:u06:toolkit,, @@ -1993304,15 +1996796,12 @@ 19:u02:Post-Processing, 13:u08:semicolon, 19:u01:Post-Processing, -9:uI2:,".-., 19:u00:Post-Processing, 15:u08:placement)., -9:uI1:,".-., 17:uI2:.."",.-.,.."., 13:u07:semicolon, 15:u07:placement)., 8:u08:"M-Y, -9:uI0:,".-., 17:uI1:.."",.-.,.."., 13:u06:semicolon, 15:u06:placement)., @@ -1994555,7 +1998044,6 @@ 11:u04:Seymore, 11:u12:seymore, 9:u14:(hmm), -7:u22:Sey, 8:u23:Seym, 11:u03:Seymore, 11:u11:seymore, @@ -1999673,17 +2003161,12 @@ 9:u11:celia, 9:u02:Celia, 9:u10:celia, -12:u14:benefit., 9:u01:Celia, 18:u08:grandchildren,, -12:u13:benefit., 9:u00:Celia, 18:u07:grandchildren,, -12:u12:benefit., 18:u06:grandchildren,, -12:u11:benefit., 18:u05:grandchildren,, -12:u10:benefit., 12:u08:insured., 18:u04:grandchildren,, 10:u14:wonder, @@ -2004257,7 +2007740,6 @@ 40:u01:nl/downloads/pub/papers/ilk0310.pdf., 10:u03:Yahoo!, 11:u06:Finance, -9:u08:Dave,, 10:u02:Sanjiv, 8:u10:das,, 10:u11:yahoo!, @@ -2004274,7 +2007756,6 @@ 10:u01:Yahoo!, 11:u04:Finance, 20:u06:abstract=276189., -9:u07:Dave,, 12:u08:gallery:, 10:u00:Sanjiv, 11:u07:Kushal,, @@ -2004283,55 +2007764,44 @@ 10:u00:Yahoo!, 11:u03:Finance, 20:u05:abstract=276189., -9:u06:Dave,, 12:u07:Pennock., 11:u06:Kushal,, 11:u11:finance, 20:u13:abstract=276189., -9:u14:dave,, 11:u02:Finance, 20:u04:abstract=276189., -9:u05:Dave,, 12:u06:Pennock., 12:u07:gallery:, 11:u05:Kushal,, 11:u10:finance, 20:u12:abstract=276189., -9:u13:dave,, 12:u14:pennock., 11:u01:Finance, 20:u03:abstract=276189., -9:u04:Dave,, 12:u05:Pennock., 12:u06:gallery:, 11:u04:Kushal,, 20:u11:abstract=276189., -9:u12:dave,, 12:u13:pennock., 12:u14:gallery:, 11:u00:Finance, 20:u02:abstract=276189., -9:u03:Dave,, 12:u04:Pennock., 12:u05:gallery:, 14:u08:(WWW2003),, 11:u03:Kushal,, 20:u10:abstract=276189., -9:u11:dave,, 12:u12:pennock., 12:u13:gallery:, 20:u01:abstract=276189., -9:u02:Dave,, 12:u03:Pennock., 12:u04:gallery:, 23:u08:http://www2003.org., 11:u02:Kushal,, 13:u08:Budapest., -9:u10:dave,, 12:u11:pennock., 12:u12:gallery:, 20:u00:abstract=276189., -9:u01:Dave,, 12:u02:Pennock., 12:u03:gallery:, 14:u07:(WWW2003),, @@ -2004340,7 +2007810,6 @@ 13:u07:Budapest., 12:u10:pennock., 12:u11:gallery:, -9:u00:Dave,, 12:u01:Pennock., 12:u02:gallery:, 14:u06:(WWW2003),, @@ -2029867,14 +2033336,11 @@ 10:u05:CITED:, 10:u04:CITED:, 10:u03:CITED:, -9:uI2:.:--., 10:u02:CITED:, 12:u08:Lachaise, -9:uI1:.:--., 10:u08:Prance, 10:u01:CITED:, 12:u07:Lachaise, -9:uI0:.:--., 10:u00:CITED:, 12:u06:Lachaise, 10:u07:Prance, @@ -2033218,7 +2036684,6 @@ 10:u06:SPARC., 9:u07:V9.V8, 13:u03:[UMIPSV],, -7:u08:2.x, 10:u10:shades, 11:u11:umips-v, 17:u12:(shade-v9.v8), @@ -2033234,7 +2036699,6 @@ 9:u06:V9.V8, 11:u07:Solaris, 13:u02:[UMIPSV],, -7:u07:2.x, 11:u10:umips-v, 17:u11:(shade-v9.v8), 13:u12:binaries., @@ -2033249,7 +2036713,6 @@ 9:u05:V9.V8, 11:u06:Solaris, 13:u01:[UMIPSV],, -7:u06:2.x, 17:u10:(shade-v9.v8), 13:u11:binaries., 10:u12:sparc., @@ -2033263,7 +2036726,6 @@ 11:u05:Solaris, 17:u08:Shade-MIPS.V8, 13:u00:[UMIPSV],, -7:u05:2.x, 13:u10:binaries., 10:u11:sparc., 9:u12:v9.v8, @@ -2033276,7 +2036738,6 @@ 10:u02:SPARC., 9:u03:V9.V8, 11:u04:Solaris, -7:u04:2.x, 17:u07:Shade-MIPS.V8, 10:u10:sparc., 9:u11:v9.v8, @@ -2033286,24 +2036747,20 @@ 10:u01:SPARC., 9:u02:V9.V8, 11:u03:Solaris, -7:u03:2.x, 17:u06:Shade-MIPS.V8, 9:u10:v9.v8, 11:u11:solaris, 10:u00:SPARC., 9:u01:V9.V8, 11:u02:Solaris, -7:u02:2.x, 17:u05:Shade-MIPS.V8, 11:u10:solaris, 17:u14:shade-mips.v8, 9:u00:V9.V8, 11:u01:Solaris, -7:u01:2.x, 17:u04:Shade-MIPS.V8, 17:u13:shade-mips.v8, 11:u00:Solaris, -7:u00:2.x, 17:u03:Shade-MIPS.V8, 17:u12:shade-mips.v8, 17:u02:Shade-MIPS.V8, @@ -2035016,7 +2038473,6 @@ 7:u22:SMC, 7:u23:SMC, 8:u04:Bugs, -10:u08:Detail, 126:u01:__________________________________________________________________________________________________________________________, 7:u11:smc, 7:u22:Bug, @@ -2035025,18 +2038481,10 @@ 126:u00:__________________________________________________________________________________________________________________________, 7:u10:smc, 8:u02:Bugs, -10:u07:Detail, 8:u01:Bugs, -10:u06:Detail, 8:u00:Bugs, -10:u05:Detail, -10:u04:Detail, -10:u03:Detail, -10:u02:Detail, 15:u08:Accelerator, -10:u01:Detail, 10:u08:[AS92], -10:u00:Detail, 15:u07:Accelerator, 15:u06:Accelerator, 10:u07:[AS92], @@ -2041590,7 +2045038,6 @@ 15:u04:-semantics., 15:u12:-semantics., 16:u14:conditionals, -7:u22:-se, 8:u23:-sem, 8:u00:cal", 15:u03:-semantics., @@ -2041665,39 +2045112,30 @@ 17:u04:inconsistent,, 17:u03:inconsistent,, 17:u02:inconsistent,, -11:u08:penguin, 17:u01:inconsistent,, 12:u08:ignator,, 17:u00:inconsistent,, 10:uI2:"!"!#!, -11:u07:penguin, 10:uI1:"!"!#!, -11:u06:penguin, 12:u07:ignator,, 11:u14:penguin, 10:uI0:"!"!#!, -11:u05:penguin, 12:u06:ignator,, 11:u13:penguin, 12:u14:ignator,, -11:u04:penguin, 12:u05:ignator,, 11:u12:penguin, 12:u13:ignator,, -11:u03:penguin, 12:u04:ignator,, 11:u11:penguin, 12:u12:ignator,, 8:u23:igna, -11:u02:penguin, 12:u03:ignator,, 11:u10:penguin, 12:u11:ignator,, -11:u01:penguin, 12:u02:ignator,, 12:u10:ignator,, 11:uI2:()!"!#!, -11:u00:penguin, 12:u01:ignator,, 11:uI1:()!"!#!, 12:u00:ignator,, @@ -2057492,7 +2060930,6 @@ 9:u02:255.3, 9:u03:41.72, 9:u05:0.158, -9:u08:43.84, 9:u10:255.3, 9:u11:41.72, 9:u13:0.158, @@ -2057506,42 +2060943,29 @@ 9:u01:41.72, 9:u03:0.158, 9:u06:257.7, -9:u07:43.84, 9:u11:0.158, 9:u14:257.7, 9:u00:41.72, 9:u02:0.158, 9:u05:257.7, -9:u06:43.84, 9:u10:0.158, 9:u13:257.7, -9:u14:43.84, 9:u01:0.158, 9:u04:257.7, -9:u05:43.84, 9:u12:257.7, -9:u13:43.84, 9:u00:0.158, 9:u03:257.7, -9:u04:43.84, 9:u08:276.6, 9:u11:257.7, -9:u12:43.84, 9:u02:257.7, -9:u03:43.84, 9:u08:44.67, 9:u10:257.7, -9:u11:43.84, 9:u01:257.7, -9:u02:43.84, 9:u07:276.6, -9:u10:43.84, 9:u00:257.7, -9:u01:43.84, 9:u06:276.6, 9:u07:44.67, 9:u14:276.6, -9:u00:43.84, 9:u05:276.6, 9:u06:44.67, 9:u13:276.6, @@ -2057631,7 +2061055,6 @@ 9:u05:263.7, 9:u06:35.81, 9:u07:0.598, -8:u08:2.89, 9:u13:263.7, 9:u14:35.81, 9:u00:0.676, @@ -2057644,7 +2061067,6 @@ 9:u03:263.7, 9:u04:35.81, 9:u05:0.598, -8:u07:2.89, 9:u08:250.8, 9:u11:263.7, 9:u12:35.81, @@ -2057652,49 +2061074,37 @@ 9:u02:263.7, 9:u03:35.81, 9:u04:0.598, -8:u06:2.89, 9:u08:37.61, 9:u10:263.7, 9:u11:35.81, 9:u12:0.598, -8:u14:2.89, 9:u01:263.7, 9:u02:35.81, 9:u03:0.598, -8:u05:2.89, 9:u07:250.8, 9:u10:35.81, 9:u11:0.598, -8:u13:2.89, 9:u00:263.7, 9:u01:35.81, 9:u02:0.598, -8:u04:2.89, 9:u06:250.8, 9:u07:37.61, 9:u08:0.187, 9:u10:0.598, -8:u12:2.89, 9:u14:250.8, -8:u23:2.89, 9:u00:35.81, 9:u01:0.598, -8:u03:2.89, 9:u05:250.8, 9:u06:37.61, -8:u11:2.89, 9:u13:250.8, 9:u14:37.61, 9:u00:0.598, -8:u02:2.89, 9:u04:250.8, 9:u05:37.61, 9:u07:0.187, -8:u10:2.89, 9:u12:250.8, 9:u13:37.61, 9:u14:0.628, -8:u01:2.89, 9:u03:250.8, 9:u04:37.61, 9:u06:0.187, @@ -2057703,7 +2061113,6 @@ 9:u12:37.61, 9:u13:0.628, 9:u14:0.187, -8:u00:2.89, 9:u02:250.8, 9:u03:37.61, 9:u05:0.187, @@ -2060047,7 +2063456,6 @@ 11:u05:Burgess, 11:u06:Dunstan, 16:u07:osteoclasts., -9:u08:Lacey, 23:u10:oliveira-dos-santos, 7:u11:tw,, 7:u14:wj,, @@ -2060055,14 +2063463,12 @@ 11:u04:Burgess, 11:u05:Dunstan, 16:u06:osteoclasts., -9:u07:Lacey, 7:u10:tw,, 7:u13:wj,, 23:u00:Oliveira-dos-Santos, 11:u03:Burgess, 11:u04:Dunstan, 16:u05:osteoclasts., -9:u06:Lacey, 7:u12:wj,, 7:u22:WJ,, 7:u23:WJ,, @@ -2060070,13 +2063476,11 @@ 11:u02:Burgess, 11:u03:Dunstan, 16:u04:osteoclasts., -9:u05:Lacey, 7:u11:wj,, 11:u14:elliott, 11:u01:Burgess, 11:u02:Dunstan, 16:u03:osteoclasts., -9:u04:Lacey, 7:u10:wj,, 11:u13:elliott, 11:u14:kaufman, @@ -2060084,25 +2063488,21 @@ 11:u00:Burgess, 11:u01:Dunstan, 16:u02:osteoclasts., -9:u03:Lacey, 11:u12:elliott, 11:u13:kaufman, 11:u06:165-76., 11:u00:Dunstan, 16:u01:osteoclasts., -9:u02:Lacey, 11:u11:elliott, 11:u12:kaufman, 11:u14:165-76., 11:u05:165-76., 10:u08:Morony, 16:u00:osteoclasts., -9:u01:Lacey, 11:u10:elliott, 11:u11:kaufman, 11:u13:165-76., 11:u04:165-76., -9:u00:Lacey, 11:u10:kaufman, 11:u12:165-76., 11:u03:165-76., @@ -2062383,22 +2065783,13 @@ 7:uI1:].), 13:u00:6000-line, 7:uI0:].), -11:u08:fourier, -11:u07:fourier, 13:u08:(Fortran), -11:u06:fourier, 13:u07:(Fortran), -11:u05:fourier, 13:u06:(Fortran), -11:u04:fourier, 13:u05:(Fortran), -11:u03:fourier, 13:u04:(Fortran), -11:u02:fourier, 13:u03:(Fortran), -11:u01:fourier, 13:u02:(Fortran), -11:u00:fourier, 13:u01:(Fortran), 13:u00:(Fortran), 7:u08:X11, @@ -2066865,9 +2070256,6 @@ 8:u11:1488, 8:u00:4638, 8:u10:1488, -10:uI2:,.[],-, -10:uI1:,.[],-, -10:uI0:,.[],-, 18:u08:query-by-query, 18:u07:query-by-query, 18:u06:query-by-query, @@ -2074508,7 +2077896,6 @@ 9:u07:Bethe, 15:u14:solvability, 15:u05:solvability, -11:u08:avenues, 12:u00:algebras, 9:u06:Bethe, 15:u13:solvability, @@ -2074517,46 +2077904,38 @@ 15:u12:solvability, 13:uI2:(,..[-])., 15:u03:solvability, -11:u07:avenues, 9:u04:Bethe, 18:u08:Algebraization, 15:u11:solvability, 13:uI1:(,..[-])., 15:u02:solvability, -11:u06:avenues, 9:u03:Bethe, 18:u07:Algebraization, 15:u10:solvability, 11:u14:avenues, 13:uI0:(,..[-])., 15:u01:solvability, -11:u05:avenues, 9:u02:Bethe, 18:u06:Algebraization, 18:u08:algebraization, 11:u13:avenues, 15:u00:solvability, -11:u04:avenues, 9:u01:Bethe, 18:u05:Algebraization, 18:u07:algebraization, 11:u12:avenues, 8:u23:aven, -11:u03:avenues, 9:u00:Bethe, 18:u04:Algebraization, 18:u06:algebraization, 11:u11:avenues, -11:u02:avenues, 18:u03:Algebraization, 18:u05:algebraization, 11:u10:avenues, 11:uI2:(.).[-], -11:u01:avenues, 18:u02:Algebraization, 18:u04:algebraization, 11:uI1:(.).[-], -11:u00:avenues, 18:u01:Algebraization, 18:u03:algebraization, 11:uI0:(.).[-], @@ -2075348,11 +2078727,6 @@ 16:u10:specializing, 16:u01:Specializing, 16:u00:Specializing, -8:u14:1984, -8:u13:1984, -8:u12:1984, -8:u11:1984, -8:u10:1984, 25:uI2:()(−)(−−)(−),, 25:uI1:()(−)(−−)(−),, 25:uI0:()(−)(−−)(−),, @@ -2089014,8 +2092388,6 @@ 27:u10:insert_normalcomparison, 8:u11:qlf,, 17:u12:c_stored_item, -6:u21:c_, -7:u22:c_s, 8:u23:c_st, 40:u00:insertabstracted_variable_comparison, 27:u01:insert_normalcomparison, @@ -2102604,7 +2105976,6 @@ 12:u08:Calarcá, 10:u11:quake,, 12:u13:armenia,, -13:u14:buildings, 10:u02:quake,, 12:u04:Armenia,, 7:u04:907, @@ -2102612,26 +2105983,22 @@ 12:u07:Calarcá, 10:u10:quake,, 12:u12:armenia,, -13:u13:buildings, 10:u01:quake,, 12:u03:Armenia,, 7:u03:907, 14:u04:destroyed., 12:u06:Calarcá, 12:u11:armenia,, -13:u12:buildings, 10:u00:quake,, 12:u02:Armenia,, 7:u02:907, 14:u03:destroyed., 12:u05:Calarcá, 12:u10:armenia,, -13:u11:buildings, 12:u01:Armenia,, 7:u01:907, 14:u02:destroyed., 12:u04:Calarcá, -13:u10:buildings, 12:u00:Armenia,, 7:u00:907, 14:u01:destroyed., @@ -2102676,7 +2106043,6 @@ 13:u05:injuries;, 13:u13:diamonds,, 13:u04:Diamonds,, -8:u08:1152, 15:u00:casualties:, 13:u04:injuries;, 13:u12:diamonds,, @@ -2102685,26 +2106051,13 @@ 10:u08:Gutié, 13:u11:diamonds,, 13:u02:Diamonds,, -8:u07:1152, 13:u02:injuries;, 10:u07:Gutié, 13:u10:diamonds,, 13:u01:Diamonds,, -8:u06:1152, 13:u01:injuries;, -8:u14:1152, 13:u00:Diamonds,, -8:u05:1152, 13:u00:injuries;, -8:u13:1152, -8:u04:1152, -8:u12:1152, -8:u03:1152, -8:u11:1152, -8:u02:1152, -8:u10:1152, -8:u01:1152, -8:u00:1152, 19:u08:nongovernmental, 13:u08:ernmental, 19:u07:nongovernmental, @@ -2176198,20 +2179551,6 @@ 11:u10:(pcci)., 11:u01:(PccI)., 11:u00:(PccI)., -11:u08:ratios., -11:u07:ratios., -11:u06:ratios., -11:u14:ratios., -11:u05:ratios., -11:u13:ratios., -11:u04:ratios., -11:u12:ratios., -11:u03:ratios., -11:u11:ratios., -11:u02:ratios., -11:u10:ratios., -11:u01:ratios., -11:u00:ratios., 10:u08:Holden, 9:u08:Micha, 9:u07:Micha, @@ -2176935,47 +2180274,38 @@ 9:u04:Paauw, 10:u06:e3018., 13:u07:Mohd-Zain, -16:u08:Transferable, 9:u03:Paauw, 10:u05:e3018., 13:u06:Mohd-Zain, -16:u07:Transferable, 9:u02:Paauw, 10:u04:e3018., 13:u05:Mohd-Zain, -16:u06:Transferable, 13:uI2:.-,,-,,,., 9:u01:Paauw, 10:u03:e3018., 13:u04:Mohd-Zain, -16:u05:Transferable, 11:u08:Moreira, 13:uI1:.-,,-,,,., 10:u08:43-76., 9:u00:Paauw, 10:u02:e3018., 13:u03:Mohd-Zain, -16:u04:Transferable, 11:u07:Moreira, 13:uI0:.-,,-,,,., 10:u01:e3018., 13:u02:Mohd-Zain, -16:u03:Transferable, 11:u06:Moreira, 10:u07:43-76., 10:u00:e3018., 13:u01:Mohd-Zain, -16:u02:Transferable, 11:u05:Moreira, 12:u08:Dziejman, 10:u06:43-76., 13:u00:Mohd-Zain, -16:u01:Transferable, 11:u04:Moreira, 12:u07:Dziejman, 10:u14:43-76., 10:u05:43-76., -16:u00:Transferable, 11:u03:Moreira, 12:u06:Dziejman, 10:u13:43-76., @@ -2210106,13686 +2213436,15093 @@ 14:u02:statistic;, 14:u10:statistic;, 14:u01:statistic;, -0=0x1.6b75d710a343ep-3 -25=0x1.6b75d710a343ep-3 -50=0x1.6b75d710a343ep-3 -75=0x1.6b75d710a343ep-3 -177=0x1.1f81473415e49p-5 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-2361=0x1.5d2850359a28dp-3 -2364=-0x1.2e70ef27a6e54p-4 -2365=-0x1.755753cf54e91p-7 -2366=-0x1.0bc09acdfbad1p+1 -2368=-0x1.f26724b759495p-4 -2369=-0x1.78a431211589cp-11 -2371=0x1.8efea6eb1281bp-25 -2372=-0x1.3d235f38c6d47p+0 -2375=0x1.4d56b2a343becp-4 -2376=0x1.41c386f3d42c2p-7 -2377=0x1.861076bc81a72p-3 -2378=0x1.e2b11a5e8aec5p-5 -2379=0x1.36a72e3bd42e8p-3 -2380=0x1.78325f9cc0d04p-5 -2381=0x1.d21f0ba869af7p-5 -2383=-0x1.b39c05f46ef2ap-9 -2384=0x1.cf3dbeeb5a853p-2 -2385=0x1.b55ec9a641bcbp-5 -2386=0x1.46c0cb34ab667p-2 -2388=-0x1.35b8ba396a7d4p-6 -2389=0x1.5fdaa58a107e9p-9 -2390=0x1.bfb1b3cd0d4fbp-6 -2391=0x1.628ae87f8cbb7p-4 -2393=-0x1.1d5edf75baea5p-8 -2394=0x1.5ae1ec8380423p-6 -2396=0x1.44359f365ff9ap-5 -2399=-0x1.7ee499d6620aap-7 -2400=0x1.0279be483dcecp-4 -2401=0x1.f6d6fefd34f2fp+1 -2403=0x1.b3a07935d24b9p-1 -2404=-0x1.3270b95efee2p+2 -2406=-0x1.d78c9023b9084p-1 -2411=-0x1.f9a812861b1eep+1 -2414=0x1.0163262925b5fp-2 -2425=-0x1.9b7099fcf6c6ep+1 -2426=0x1.fa89c3b194e23p+1 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-2486=-0x1.70c835d683e73p+2 -2491=0x1.051c5c0a6d60fp+0 -2500=-0x1.1953fa58c131fp+0 -2501=-0x1.cfd67c6de38fap+2 -2502=-0x1.6fa8e3e05cadp-1 -2503=-0x1.2ca58058c487p+2 -2504=0x1.6ac37aaf4fccbp+1 -2505=-0x1.62d365c9c67fep+0 -2506=-0x1.725923226c878p+2 -2507=0x1.81895adc33a3cp-4 -2508=-0x1.ad4429713d242p+0 -2509=0x1.ed57d2094ab2ep-3 -2510=-0x1.bad81b11c3bb8p+0 -2511=-0x1.443210f40f314p+3 -2512=-0x1.04fc81d4d8e2p+0 -2513=-0x1.59244d7d54278p-1 -2514=-0x1.4b54c1e8178a2p-1 -2515=-0x1.d173601231833p+0 -2518=-0x1.313f729036b5fp+0 -2519=-0x1.dbfa14accf7b6p+0 -2520=-0x1.2a6f20d5d120cp-17 -2521=-0x1.ac1ca01d508ap-2 -2524=-0x1.70001918c76f8p-4 -2529=-0x1.35c0ba108077ep+1 -2530=0x1.8e7d507e0392p-1 -2531=0x1.32aa5d67d279fp+3 -2534=0x1.3d8306bee4ddap+0 -2536=-0x1.32e31cc66cb73p+1 -2550=-0x1.f96cc816bb27p-3 -2551=-0x1.57fe1ef31fb34p+2 -2553=-0x1.960dc165f6e9ap-3 -2554=-0x1.09219afba6b1ap+3 -2555=-0x1.dd8f1044f9ed5p+1 -2556=0x1.a6ed17b02b07fp+2 -2557=-0x1.3044550e5d04fp-1 -2559=-0x1.fa10ed5b52777p-5 -2561=-0x1.e3a0d153208b6p+2 -2564=-0x1.93f290af94a36p-3 -2566=0x1.0d145a834bcdfp-2 -2569=-0x1.cad0a28bb3d4bp-1 -2570=-0x1.596dc0ea22f8cp-5 -2579=-0x1.ff38afe9042aap+0 -2580=0x1.85ecfc69cb602p+0 -2583=0x1.8ea6cc18abbf7p+3 -2586=-0x1.1427c2acbe976p+1 -2600=0x1.f61b2ebbfc5b9p-3 -2601=-0x1.0893b7b81a8d5p+2 -2602=0x1.8342fbf64719p-14 -2603=-0x1.d698b9b84c332p-2 -2604=-0x1.88d7534ed032ap+2 -2605=0x1.3ba978e356c6bp-2 -2606=-0x1.6a805c949e67ap+1 -2607=-0x1.c8268e13766f8p-1 -2608=0x1.2a90e32ccacebp+3 -2609=-0x1.c3e0ed1a7db74p-6 -2610=0x1.22c6ded0e7b46p+0 -2611=-0x1.4958a4df3d39fp+2 -2626=-0x1.6a0a9902a65aep+2 -2627=0x1.47dcf73b41b8p+1 -2628=0x1.217bcca4a43dep+0 -2629=-0x1.e36975826ddcdp+2 -2631=-0x1.3f799ee941952p+1 -2634=-0x1.4ace31064134fp-1 -2635=0x1.8898e5b7e326p-2 -2636=-0x1.97422b4bfaf9fp+2 -2639=0x1.ed7457a623601p+0 -2640=-0x1.253ce073baf5ep-1 -2641=0x1.df9bef429c466p+2 -2644=-0x1.6189ea426df13p-8 -2648=0x1.bed6d28d287f8p-2 -2651=-0x1.0e02f674a3163p+2 -2652=0x1.b968999748d12p-3 -2653=-0x1.04fc0fec34b9dp+0 -2654=-0x1.52443d824ebd8p+2 -2660=-0x1.3548dd410de95p-25 -2661=0x1.87ba5feaaf3d8p+1 -2670=0x1.7a047a6fd2a78p-1 -2675=-0x1.cde2b3ae5f16bp-2 -2676=-0x1.9aeeb7d4a2f4ep+2 -2677=-0x1.9195a112aade7p-3 -2678=-0x1.68120996fbd16p+1 -2679=-0x1.40d213e423164p+3 -2680=-0x1.f55317227f08ap-1 -2681=-0x1.08f481abbcf89p+2 -2682=-0x1.17c9b296e01c1p-1 -2683=-0x1.ff30c61f55e4bp-3 -2684=-0x1.6a413288e8f9fp-3 -2685=-0x1.2e358b42f2781p-1 -2686=0x1.003eda7347a35p+1 -2689=-0x1.92e8a91bef27dp-1 -2690=-0x1.05633ea834e5p-1 -2694=-0x1.0fca180d7d2bbp+1 -2695=-0x1.7c671118726b3p-4 -2704=-0x1.46e8a6012d24bp-1 -2711=-0x1.f8efebe9ca0dp-2 -2713=0x1.59106cebb9d98p+3 -2720=0x1.84259ac83a723p+0 -2726=-0x1.6899056f315b7p-1 -2729=-0x1.bf9f292ad3714p+1 -2732=0x1.d75dcd3cbd673p-6 -2735=0x1.d690505bbbc49p+0 -2736=-0x1.d3bfb0a64af46p+1 -2738=0x1.3d1cc3f567e11p+3 -2745=0x1.7144b5f6d9dd9p+0 -2750=-0x1.36b7db22879ebp-1 -2751=-0x1.1312b215dc5e7p+2 -2752=0x1.2d5286dcc2f7ep+0 -2753=0x1.96682eebf7275p-1 -2754=-0x1.c30c9b7f7288p+2 -2755=0x1.8d2e11172128ap-2 -2756=-0x1.4704d989c969cp+1 -2757=0x1.5aaab3a42decp-2 -2759=0x1.2f1d871c04635p+0 -2760=-0x1.30f200f63f053p-8 -2761=-0x1.6adc6699a5229p+2 -2764=0x1.2aa858b247e76p+1 -2765=0x1.f65488f0f9a27p+2 -2775=-0x1.46de82bf36e51p-1 -2776=-0x1.df28507e6ccbfp+1 -2777=0x1.5a905678059f4p-1 -2779=-0x1.eebcd948bcc3ap+2 -2781=-0x1.168cef09f04f7p+1 -2784=0x1.58c1141e87dc3p+0 -2786=-0x1.7387849e86bb8p+2 -2789=0x1.8bc5f531e5dap+0 -2790=0x1.f0dd7ef901e7fp+2 -2794=0x1.39d158b4c27b8p-4 -2801=-0x1.0ab106b8e099ap+2 -2802=0x1.ce4b74c951839p+0 -2803=0x1.1aed94d53439ep-2 -2804=-0x1.a11a6782afbf3p+2 -2806=-0x1.2f54d4c6810cep+1 -2809=-0x1.81ddcb964b22ap-1 -2811=-0x1.e714e0b6be0fp+2 -2814=0x1.a795cb7a5f169p+0 -2815=0x1.3913e85152621p-2 -2816=0x1.ee9cbb052142bp+2 -2819=0x1.43faa0c485f19p-2 -2843=0x1.33c911a9a6456p+3 -2850=0x1.1ce61f76c26b8p+1 -2851=-0x1.e8f96933f8127p-1 -2854=-0x1.e11ad1085679fp-1 -2868=0x1.71f225869ef0ap+3 -2876=-0x1.8b8132f4563dap+1 -2878=0x1.d150a7d93f28p-9 -2879=-0x1.c11fa811ccdc4p+2 -2881=-0x1.f90d48a179ab6p+0 -2884=0x1.3d4016d814ae6p+0 -2886=-0x1.827d27e65c436p+2 -2894=0x1.878094de2db65p+2 -2904=-0x1.fc2617592ecd4p+0 -2910=0x1.dc4ea04834d4dp+0 -2911=-0x1.7b8cc4e5ac96cp+0 -2921=0x1.87fe81bca0251p+3 -2925=0x1.ca92d9bc2a7aap-2 -2926=-0x1.05974139ddd81p+1 -2929=-0x1.70410dd2ada36p+2 -2931=-0x1.d99d7952424dap-3 -2932=0x1.5c8cdcee072fep-1 -2935=0x1.45b5520570443p+0 -2936=-0x1.518d5653588c8p+2 -2939=-0x1.ce584889d0139p-3 -2945=0x1.a49882e97b3c3p-1 -2946=0x1.490a652e63d7dp+3 -2954=-0x1.157ec2e87d40dp+1 -2959=0x1.43ca99c6228bep+0 -2960=0x1.0ca1f14f2cdd7p+0 -2961=-0x1.c2cc71f9c25b8p+0 -2972=0x1.c907f8f7f19d7p+1 -2999=0x1.829c4a4c68c69p+3 -3001=-0x1.8e94ce95e1f65p+0 -3004=-0x1.35564dde70016p+1 -3011=-0x1.003749ac669c7p+0 -3024=0x1.41aff410ff2bep+3 -3026=0x1.7427e03133dfap-2 -3027=-0x1.031d9c07524c5p-1 -3043=0x1.7160ec9783e59p-2 -3051=0x1.7427e03133dfap-2 -3052=-0x1.031d9c07524c5p-1 -3068=0x1.7160ec9783e59p-2 -3076=0x1.7427e03133dfap-2 -3077=-0x1.031d9c07524c5p-1 -3093=0x1.7160ec9783e59p-2 -3156=0x1.5f6cebacc1993p-14 -3175=0x1.eac18f916bb71p-3 -3176=-0x1.e60e08354e8a2p-3 -3177=0x1.0cf0c67754213p-1 -3178=-0x1.5626cbcf5eb0ep-7 -3179=0x1.41c32cd05178dp-10 -3185=-0x1.163b1ac8c196ep-11 -3186=0x1.dbdefa55e7705p-7 -3189=0x1.001432f7ea594p-1 -3190=0x1.d2e2a478826e5p-6 -3191=-0x1.af1a504a07511p-5 -3193=-0x1.4a0bb44bdcfaep-3 -3501=0x1.192a0e91adfd1p-5 -3504=-0x1.05d5b354e9f5ap-9 -3511=-0x1.9bb00c914bcc9p-7 -3515=0x1.863edbf7dfc43p-3 -3525=-0x1.79fef1eea70c9p-1 -3526=-0x1.888a51834d99dp-4 -3527=0x1.a917ce5b39cf4p-1 -3529=-0x1.31cc585902403p-6 -3530=-0x1.0fb81be917093p-2 -3534=0x1.0d0d2bd34d398p-1 -3535=0x1.d13482bff1fefp-2 -3536=0x1.96169dde0123dp-6 -3539=0x1.233d01cc14b6dp-5 -3540=0x1.a65027f0f983dp-1 -3541=-0x1.2669a6caed2dbp-3 -3553=-0x1.00a15632b39d2p-1 -3554=-0x1.94b3351c27af4p-7 -3559=-0x1.8f9173b7087c1p-3 -3560=0x1.6f03837a23eabp-2 -3561=0x1.0bbec07179901p+0 -3569=0x1.dca6cc33deddap-2 -3625=-0x1.e6c7f0563b82fp-26 -3626=-0x1.79d8dfe506516p-12 -3627=0x1.b90a1b666ebdcp-14 -3628=0x1.d0b9554df7e6dp-5 -3629=0x1.f8f2d18f202a1p-8 -3631=-0x1.e887b48515cdcp-9 -3633=-0x1.3acad3cea5e8cp-4 -3635=0x1.b5eda232261b5p-12 -3636=0x1.2b481c037dfedp-4 -3640=0x1.d0e527c3644afp-6 -3641=-0x1.a73a3f21acf02p-22 -3643=-0x1.40d0af48bd371p-4 -3644=-0x1.5249b378303fap-14 -3646=-0x1.f569cad495a46p-2 -3647=0x1.45c02ef42defep-2 -3651=-0x1.8be2c06be00ddp-9 -3652=-0x1.bc8b5858a4b1dp-1 -3653=-0x1.1983a23cb215bp-3 -3654=0x1.693327e79410fp-4 -3656=0x1.54b37bdd534e3p-3 -3658=-0x1.23cd0c1fb8c89p-3 -3659=-0x1.74d63774addbdp-4 -3660=-0x1.4bf0fc829f4b8p+0 -3661=-0x1.726dfd2cffc26p-7 -3664=-0x1.15f742cc4795fp-3 -3665=-0x1.740167188f397p-2 -3669=-0x1.24f2215622e54p+0 -3671=-0x1.19d60c80c22fp-1 -3675=-0x1.777c83ff10052p-1 -3676=-0x1.2089cbbd40566p-5 -3678=-0x1.c35a90b1e9852p-2 -3679=0x1.100f418d902e3p-7 -3680=-0x1.f607a6a1f32fap-2 -3681=0x1.98c7271b1d791p-7 -3685=0x1.8bcbee956417cp-7 -3686=0x1.02e072045fe0ep-4 -3688=-0x1.70ff85740af17p-15 -3689=-0x1.bbfb6aa12bfa5p+0 -3690=-0x1.5057e90143dc4p-3 -3691=0x1.f55f9bc670bb3p-4 -3692=-0x1.30d61fad18ae4p-2 -3693=-0x1.a5ae83eb35737p-4 -3694=-0x1.56869d1e7fd7dp-4 -3696=0x1.e5a2368eed911p-4 -3700=0x1.39ead7efec56p-2 -3701=0x1.59711cd40ecp-2 -3702=0x1.208153170882ap-2 -3703=-0x1.9d18c5e40ed89p-7 -3704=-0x1.8368e4c54e318p-4 -3706=-0x1.ae5da0c443887p-1 -3708=0x1.e9cce72ecfbb8p-27 -3709=0x1.981999fdfd1f2p-2 -3711=-0x1.5bb4834adcb8dp-4 -3714=0x1.0aeb8d87916f2p-3 -3715=-0x1.0b5f5e5b8ef1fp-3 -3716=0x1.526f57cdd3d6ep+0 -3724=-0x1.28445efbb026ep+0 -3726=-0x1.3711ecd6ca7efp-10 -3727=-0x1.07cc5b87f4affp+1 -3728=-0x1.0225bfdc2110ep-4 -3729=0x1.94a03282e60dap-4 -3731=0x1.7a7df585670eap-6 -3732=-0x1.b607d3dbc3e1p-3 -3735=-0x1.6a0c601beac4p-5 -3736=0x1.6f0ff9c5cd296p-3 -3739=-0x1.115b9b4b1c814p-7 -3740=0x1.06648e9e68bfcp-7 -3741=0x1.10e91d20c387ep-6 -3743=-0x1.2e26117da0c4ep-8 -3744=-0x1.63a1e03056f41p-8 -3746=0x1.06b1919bb6276p-24 -3747=-0x1.6d6bc367275b9p+0 -3750=-0x1.57676c08ea4fep-1 -3751=-0x1.44ee3b9f31d1bp-3 -3752=0x1.501f232097e23p-2 -3753=-0x1.6c6f54acfe4e5p-1 -3754=0x1.ac67e285f38f2p-9 -3755=-0x1.125048e8f8462p-1 -3756=-0x1.0d3fa1b013236p-4 -3757=-0x1.5bf62edc09bfp-6 -3758=-0x1.412a2201fa6bbp-2 -3759=0x1.1e284f7585498p-2 -3760=-0x1.cfc0b1fb35568p-2 -3761=0x1.3df0e6b780984p-8 -3764=-0x1.8936e0fccd7f6p-2 -3765=-0x1.42aa41f353c9p-4 -3768=-0x1.cbf24edd78393p-4 -3769=-0x1.e2094b7d24a0dp-7 -3770=-0x1.3a3b953510bf2p-2 -3772=-0x1.d6e60ac2bc77bp-1 -3773=-0x1.66594856ec6b7p-2 -3775=-0x1.3ffd5907bfec6p-1 -3776=0x1.72735bb3bfb7ep-10 -3777=-0x1.652de8b696bbfp-2 -3778=-0x1.307239388f4b5p-2 -3779=0x1.9e461bf1a4af3p-4 -3780=-0x1.c3c2c301a2d57p-2 -3781=0x1.ac5868d6389d9p-5 -3782=-0x1.3cbb7f4115372p-25 -3783=-0x1.6f90ff5cf0f7dp-11 -3785=-0x1.61d82fce84573p-1 -3786=0x1.4ac795cf2c0ep-3 -3787=-0x1.ad0fcaa4d5fadp-1 -3788=0x1.2ef2f91aa88e7p-26 -3789=-0x1.ed7a8ddd83672p-25 -3790=0x1.b62f6108dba64p-6 -3791=0x1.111790adee76ep-6 -3793=-0x1.2ac657fff455dp-21 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-4302=0x1.3ad0d4ee425e2p-7 -4303=-0x1.ead4109fe91dfp-6 -4304=0x1.57d95601c5b45p-3 -4305=-0x1.20a26bf151f36p-2 -4306=0x1.bd4c3a51ad402p-4 -4308=-0x1.7aebde3fa1277p-7 -4309=0x1.0441c703123c8p-2 -4310=0x1.049717426e946p-6 -4311=0x1.5180448506e32p-2 -4313=0x1.5271cc0c9e6dcp-23 -4314=0x1.0c8c9199aa26cp-3 -4315=0x1.92275b75b9b9cp-6 -4316=0x1.41667e49e50bdp-2 -4317=-0x1.ee3fc9f882259p-2 -4318=-0x1.e841a40ab6202p-7 -4319=0x1.0c6cc0215cd84p-6 -4321=0x1.33b7c4233d46ap-23 -4322=-0x1.4af44b958152dp-4 -4323=-0x1.b3fe78821f18dp-1 -4324=-0x1.75be872413458p-4 -4325=0x1.81e2e9d8dc4e1p-4 -4329=-0x1.d1d10df89fd47p-2 -4340=0x1.1a66df2d921c1p-4 -4343=0x1.315a91d01f335p-3 -4350=0x1.81e2e9d8dc4e1p-4 -4354=-0x1.d1d10df89fd47p-2 -4365=0x1.1a66df2d921c1p-4 -4368=0x1.315a91d01f335p-3 -4451=0x1.2b366680066cbp-3 -4452=0x1.950b89bd126f8p-3 -4453=0x1.de08afea82504p-4 -4454=0x1.db073b7a22454p-9 -4456=-0x1.35674594b47e6p-2 -4459=0x1.addc65e5b65a1p-3 -4461=-0x1.f0152d2887e9ep-7 -4464=-0x1.66176cd434978p-1 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-5111=0x1.36ce96570e2b9p-5 -5113=-0x1.779d115869d66p-21 -5114=-0x1.eb8820ea64e27p-7 -5116=0x1.45ce1bbb490c9p-2 -5119=0x1.ba166112b8b51p-5 -5120=0x1.a27c12211f17cp-3 -5125=-0x1.352dd2051b847p-2 -5126=0x1.7819d33055ba5p-10 -5127=0x1.716875b88c37p-1 -5128=0x1.f3a2c0ff8abd6p-6 -5129=0x1.754837338a548p-5 -5130=-0x1.d156f893a667p-3 -5131=-0x1.584f8a2ebeea7p-8 -5132=-0x1.27c13f26970b1p-3 -5133=-0x1.9ffc5ac1c45eep-6 -5135=-0x1.055eed4b2e319p-1 -5136=0x1.059ff81a17cb8p-4 -5137=-0x1.0e5c694540fadp-1 -5138=-0x1.6dae025c73aedp-3 -5139=0x1.261833241bd09p-1 -5140=0x1.4fcf91081a57bp-4 -5141=-0x1.290a4de55f07p-26 -5143=-0x1.9264386ff08c8p-24 -5144=0x1.2b701652f39dp-10 -5145=-0x1.3e47f5f139e2p+0 -5151=-0x1.37e8471192192p-21 -5152=-0x1.7871ca9a608cdp+1 -5153=-0x1.b9ec134e8ca25p-1 -5154=0x1.387242460c42fp-5 -5155=-0x1.bea88c3c6a0fdp-2 -5156=-0x1.80a27523f7391p-7 -5160=0x1.a1914befd091p-2 -5161=-0x1.00215cb13d553p-6 -5164=-0x1.3d2736fe2c2e5p-29 -5165=0x1.fb74830b1b843p-3 -5166=-0x1.2216b4c56b0f1p-1 -5169=-0x1.bc0c6b6eb0ee5p-3 -5175=-0x1.71376ebdc3921p-3 -5176=0x1.3d400f151ddbap-3 -5177=0x1.1c914175d67cep-1 -5178=-0x1.37e53f5244be1p-2 -5179=0x1.506d8ed66766ap-5 -5181=0x1.bfb4ac88f7f66p-6 -5184=-0x1.e5c2c68018477p-3 -5185=-0x1.344cf33e80e63p-1 -5186=0x1.cbda8b1a557b2p-8 -5189=0x1.9a238adda64fep-5 -5190=-0x1.0d010baea6b5bp-1 -5194=-0x1.d3c763e528a45p-3 -5200=-0x1.e8c413562c652p-4 -5201=0x1.523787dd036bdp-8 -5202=0x1.1274241448c2cp-3 -5203=-0x1.e82d559523c69p-4 -5204=-0x1.42eeb98ae612ap-7 -5205=0x1.522e0d4b59cd1p-24 -5206=0x1.e2bcbe9e6ded5p-5 -5209=0x1.06b1ae23cb7aep-4 -5210=-0x1.a9835a7aab593p-2 -5211=0x1.57caa67e56d0ep-4 -5212=-0x1.df95e225b289p-29 -5213=-0x1.32c3701e4c9aap-4 -5214=0x1.56fa94406a118p-4 -5215=0x1.aa98dd59a25cep-6 -5216=-0x1.8fa2a86294f71p-3 -5218=-0x1.522121da2f092p-7 -5219=0x1.1807454f0a61cp-4 -5220=-0x1.333318cdb2fb1p-1 -5223=-0x1.d7ae97e346abbp-3 -5224=-0x1.924e3116748ecp+0 -5225=-0x1.b66a8a8ed2ecep-6 -5226=0x1.c043dd18501edp-5 -5227=0x1.d78bc6b9f259fp-8 -5228=-0x1.7d2905f8ae5aap+0 -5229=0x1.951b477eb0dc1p-8 -5230=-0x1.9504a8641b4b7p-1 -5231=-0x1.e4e666fbeb52ap-4 -5232=-0x1.2a598ef3ea965p+0 -5234=0x1.65aaf548ddecep+1 -5235=-0x1.3b164391ba7ebp+0 -5236=0x1.5d812857375b2p-6 -5238=0x1.7afae46992ed4p-5 -5239=0x1.5f7f77a5d542fp+0 -5240=0x1.223688671a8cep-1 -5241=0x1.3f3a98aab3f5fp+0 -5243=-0x1.f007cdd282c87p-15 -5244=-0x1.361bfbc474f39p-6 -5245=-0x1.087440b6200f3p-2 -5300=0x1.591c38ceb7f52p-1 -5301=0x1.1d22fe838074bp-5 -5303=-0x1.a296df107c5ap-2 -5304=-0x1.2c6035afd6363p-5 -5306=-0x1.071e6defc8304p-8 -5308=0x1.be0df415a54f1p-6 -5309=-0x1.0060dc11c69edp+0 -5311=0x1.684d3cd96902dp-8 -5315=-0x1.8d160cc81b992p-4 -5316=-0x1.0cd0bc79c494fp+0 -5319=-0x1.9a0f66ea96fa7p-6 -5325=-0x1.3f4a55f522145p-3 -5326=-0x1.829e6b1f27116p-6 -5327=-0x1.965f0be907c71p-4 -5328=-0x1.3ea645c8c7063p-3 -5329=-0x1.3a836f0d462cdp-5 -5330=0x1.41688099768a3p-2 -5331=0x1.4573d7905e822p-6 -5333=-0x1.5f93d300f2abap-2 -5335=-0x1.0b923f7e7490fp-2 -5336=0x1.9882212b22ffcp-5 -5339=-0x1.5448c992c9059p-1 -5341=-0x1.f441f24712087p-8 -5344=0x1.7df28d032e4e6p-2 -5350=0x1.7a3fe8978ec68p-3 -5351=0x1.481ca6c4b45adp-4 -5352=0x1.f67d682d5788cp-3 -5353=0x1.5cdc46a7907b1p-3 -5354=-0x1.863ef7375657bp-8 -5355=0x1.abdad3b4614cp-2 -5356=-0x1.931ae53d6fe58p-3 -5357=-0x1.362e4803a1816p-7 -5358=-0x1.e6d263579f524p-4 -5360=0x1.4450058f73ba8p-2 -5361=0x1.565cc8f2f51e8p-6 -5364=-0x1.aa29813c0a25p-6 -5365=0x1.4d5fac2bc4e04p-5 -5368=-0x1.78041c02dbaap-2 -5369=-0x1.0cfc5bff993b2p-14 -5371=0x1.239bda79696e3p-5 -5375=0x1.1f69cee8dae51p+0 -5376=0x1.725c0fb1eddabp-2 -5377=-0x1.d436311626de9p-3 -5378=0x1.17a158b9a685ap-3 -5379=-0x1.1239d5359283fp-8 -5380=-0x1.ce3459c22f877p-5 -5381=-0x1.3b77bc4e96262p-2 -5382=-0x1.431013b26c28dp-7 -5384=-0x1.76370646fe876p-1 -5385=0x1.b91e18040ff56p-6 -5386=0x1.c1c3eb8f15bd5p-10 -5388=-0x1.1fdaace09f453p-1 -5389=0x1.9789a129e5a51p-2 -5391=-0x1.6c9b2d3887f95p-2 -5392=-0x1.016937a451e86p-3 -5394=-0x1.241c9e7e0409cp-23 -5396=-0x1.2bad0d2b29d7ap-1 -5399=0x1.25d76fc0d6245p-2 -5401=0x1.acc0ca94b27dbp-3 -5403=-0x1.eabc0dbc52d7p-5 -5404=-0x1.ae7b758dd4e65p-5 -5418=0x1.03f35c244e655p+0 -5419=0x1.ba691fe9a85ap-2 -5500=0x1.b82e8d83de283p-3 -5501=-0x1.27e5fc972257fp-9 -5503=0x1.5a76112acb8cap-1 -5504=-0x1.619e2c17542acp-9 -5511=0x1.f4d9170475e5p-7 -5514=-0x1.e9577406c9112p-1 -5515=0x1.1dcf2d78cd878p-1 -5516=0x1.75bedf8ceac3cp+0 -5518=-0x1.8b0a4ffffb904p-8 -5519=-0x1.8ccf1fadd8a2p-26 -5525=0x1.73025aa6a16efp-1 -5600=-0x1.44492e5d92d1cp-4 -5601=0x1.08aefcc42272dp-7 -5602=0x1.23e1f0cf8a0ecp-2 -5603=-0x1.f0b1a16c8fdfp-4 -5604=0x1.9c534122c0079p-8 -5606=-0x1.587d48c595c6ap-2 -5609=0x1.fa755c8110a1ap-4 -5611=0x1.77255e90132a8p-7 -5614=0x1.6e01b3f19f1fep-3 -5615=-0x1.a616abdb46c2bp-3 -5616=-0x1.4d6d74d9d3204p-5 -5618=-0x1.7e6b3a3739e3ep-3 -5619=-0x1.be48deffadd66p-3 -5624=-0x1.320514c042d97p-1 -5629=0x1.12c19aee78f39p-3 -5851=-0x1.8539770e02447p-3 -5852=-0x1.4738e57343876p-5 -5854=-0x1.8dee411fe4191p-4 -5855=0x1.d06193c25a663p-8 -5857=0x1.d00164ac3037bp-4 -5859=0x1.a541e2b4ab261p-3 -5861=-0x1.c8b492ce7653dp-13 -5864=0x1.bdc634e2965a6p-6 -5865=0x1.12d23b324c07ep-2 -5869=-0x1.6f8d2a97e4d7fp-6 -5925=0x1.1982f503d5925p-3 -5926=-0x1.712d47db59c25p-3 -5927=-0x1.8c69c0e91df96p-13 -5928=0x1.5a6de5bfcec2ap-3 -5929=0x1.e43c7b2eda9b2p-11 -5931=0x1.65307db2f03d7p-6 -5934=-0x1.a89616acb55f4p+0 -5936=-0x1.36eb9be27976p-5 -5939=0x1.6f1f67029bc09p+0 -5941=-0x1.a174647a6c7bbp-2 -5951=-0x1.8539770e02447p-3 -5952=-0x1.4738e57343876p-5 -5954=-0x1.8dee411fe4191p-4 -5955=0x1.d06193c25a663p-8 -5957=0x1.d00164ac3037bp-4 -5959=0x1.a541e2b4ab261p-3 -5961=-0x1.c8b492ce7653dp-13 -5964=0x1.bdc634e2965a6p-6 -5965=0x1.12d23b324c07ep-2 -5969=-0x1.6f8d2a97e4d7fp-6 -5976=-0x1.8539770e02447p-3 -5977=-0x1.4738e57343876p-5 -5979=-0x1.8dee411fe4191p-4 -5980=0x1.d06193c25a663p-8 -5982=0x1.d00164ac3037bp-4 -5984=0x1.a541e2b4ab261p-3 -5986=-0x1.c8b492ce7653dp-13 -5989=0x1.bdc634e2965a6p-6 -5990=0x1.12d23b324c07ep-2 -5994=-0x1.6f8d2a97e4d7fp-6 -6001=-0x1.8539770e02447p-3 -6002=-0x1.4738e57343876p-5 -6004=-0x1.8dee411fe4191p-4 -6005=0x1.d06193c25a663p-8 -6007=0x1.d00164ac3037bp-4 -6009=0x1.a541e2b4ab261p-3 -6011=-0x1.c8b492ce7653dp-13 -6014=0x1.bdc634e2965a6p-6 -6015=0x1.12d23b324c07ep-2 -6019=-0x1.6f8d2a97e4d7fp-6 -6025=0x1.e52decbb5a378p-3 -6026=0x1.eb2891235e7bap-8 -6028=0x1.8a68f553f0f1ap-2 -6029=0x1.48cd0d5420e1ep-6 -6030=0x1.40a6d745ea919p-2 -6031=-0x1.46f4401866f34p-6 -6034=-0x1.7a70f00633379p-2 -6036=0x1.71380284a8171p-5 -6038=0x1.b31656f2c5b7dp-27 -6039=0x1.1fdcec696f136p-1 -6040=0x1.9e94f0f4a97b4p-4 -6041=-0x1.6ff4ce0bb937p-5 -6044=0x1.66eb3ea0571b7p-4 -6046=-0x1.87d88fc5124a3p-4 -6049=-0x1.17fc78dbf2a75p-4 -6051=0x1.61e9f4f7e5d6fp-3 -6053=-0x1.fa5c4a2dc768bp-3 -6054=-0x1.0e8aec0f9cde7p-5 -6055=0x1.589618456945ep-2 -6056=0x1.7b58519da0391p-2 -6058=-0x1.458cd8d53a882p-3 -6059=0x1.8610e714f4745p-5 -6061=-0x1.f943ea9efce4dp-12 -6064=0x1.0f5960c93db6dp-1 -6065=0x1.184ad32d956fdp-1 -6066=0x1.39325ac1964a1p-1 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-7156=0x1.c657b6e42fc7ap-6 -7157=0x1.6c37c8840a78bp-2 -7158=-0x1.fc383cddc9529p-26 -7159=0x1.1ca0fa525b2efp-3 -7160=-0x1.5da094e4eafc5p-9 -7161=0x1.f3ab6bcb0b52ep-5 -7163=-0x1.0ff9ce9232917p-7 -7164=0x1.23f7e9c9dd9a2p-2 -7165=0x1.5ba8fe09f8bc3p-4 -7168=-0x1.39aa3a16bff5bp-23 -7169=0x1.610918d3f66aap-4 -7170=-0x1.0402f12a11871p-5 -7171=-0x1.bccc51ed960f2p-2 -7174=-0x1.e7bece42d802cp-1 -7176=0x1.374e7b74a4bd1p-3 -7177=-0x1.191aad8ac0c87p-1 -7178=0x1.25f15651832fbp-1 -7179=-0x1.615fce0340191p-4 -7181=-0x1.829dc4ae5cf91p-5 -7182=0x1.07910623a87d9p-3 -7184=0x1.a7e7129ee7333p-3 -7185=0x1.18ad97032c7ffp-2 -7186=-0x1.08dc9cb20deafp-6 -7190=0x1.121050178f609p+0 -7194=-0x1.85da5eaedf418p-26 -7196=-0x1.034aba159e6ffp+0 -7197=0x1.d4ddec222e4a1p+0 -7201=-0x1.7ed292ba45dd9p-6 -7202=-0x1.a3b3931d7e309p-3 -7203=-0x1.b28fed403b11dp-4 -7204=0x1.0b6a9243a199ap-5 -7206=-0x1.3ef312b1ac6d1p-4 -7210=-0x1.2224924298c24p-1 -7211=0x1.a3f76f9d6b8c7p-7 -7214=-0x1.4e685548b018ep-3 -7215=0x1.c48398d1cec96p-4 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-17953=-0x1.5f567115618bep-4 -17954=0x1.0d89ecb2ea70cp-6 -17958=0x1.69de305a56272p-6 -17959=0x1.11b2b06a24d67p-1 -17961=-0x1.3f6f661a54a68p-6 -17963=-0x1.6cccba9dc8ac3p-2 -17965=-0x1.44965a65fa84ep-2 -17966=-0x1.0fb1bbec40b72p-7 -17969=-0x1.5676ba063e5a7p-3 -17970=-0x1.1cb4cc5e8511fp-1 -17971=-0x1.426c2a2c1e217p-5 -17975=-0x1.f810b8fc5495dp-2 -17976=0x1.ad485baf91dcep-6 -17977=-0x1.02f89ca70597fp-1 -17978=0x1.e7e58797e3129p-7 -17979=0x1.1826bd82e0ab4p-5 -17980=-0x1.5f8cace1ed285p-5 -17981=-0x1.d0326af522b6cp-3 -17986=0x1.0dbc9f6973bep-5 -17990=0x1.ac59d9bb3aaaep-3 -18025=0x1.4626332f8bf6dp-2 -18026=-0x1.843617cb9e6dfp-6 -18027=-0x1.378906db35e8fp-5 -18028=-0x1.30e113ce16665p-3 -18029=0x1.e72ffe2a6c78cp-7 -18030=-0x1.d5856fdc3364fp-2 -18031=0x1.cbc6943d06ee9p-5 -18033=0x1.c9f7df1fa4e8dp-5 -18035=-0x1.5a6e4f112df9p-4 -18036=0x1.26c7f2af3cd9dp-6 -18038=0x1.6cca2afcae9e3p-9 -18039=0x1.bfb81ec39325ap-4 -18040=0x1.0b255ed67f106p-4 -18041=-0x1.0dd3abcc0315ap-6 -18043=-0x1.af68e9c496abp-6 -18044=0x1.db5d329632d9cp-23 -18046=-0x1.f4dad1155db3fp-3 -18048=-0x1.5e7823565db37p-6 -18226=-0x1.e5a948a24121p-24 -18229=-0x1.37d944980c338p-9 -18231=-0x1.0b3e0393712adp-5 -18233=0x1.20a8b0f358985p-2 -18234=-0x1.684ab46e05c88p-2 -18236=-0x1.a6de078a6dce4p-11 -18241=0x1.6756d11a33e4p-4 -18244=-0x1.83cfdf6dc7281p-2 -18301=0x1.c71529c68f948p-1 -18304=-0x1.0b40183c435a2p-1 -18316=0x1.3e5b3b0e81c5bp+0 -18324=0x1.2e468f25ffbbep-1 -18501=0x1.1f94662be0b25p-4 -18502=-0x1.ae8eab9577c46p-4 -18503=-0x1.e00e5c47923f6p-3 -18504=0x1.103bca6dce727p-7 -18506=0x1.661d55d04090ap-2 -18509=0x1.0ddca247e48b5p-2 -18510=-0x1.3b4fc91df5272p+0 -18511=-0x1.29c65ef818e11p-8 -18515=0x1.95bf9ca20cd39p-4 -18518=-0x1.d06c235f90b16p-4 -18521=-0x1.959efcab63aeep-4 -18525=0x1.ee21af08974bep-4 -18526=0x1.c2a1e59cf7d6bp-5 -18527=0x1.ec711314febedp-1 -18528=-0x1.1e1d32e751182p-3 -18529=-0x1.fc1dc091f277dp-5 -18531=-0x1.fef92a872ad6fp-2 -18532=-0x1.bf2040102e02ep-3 -18534=0x1.2a3cef18ad1bep-2 -18536=-0x1.0ab3470b632a9p-4 -18539=0x1.e59faa7628d2ep-1 -18540=0x1.2c825c0400b0ep-2 -18541=-0x1.d63c1f54e03ep-26 -18543=-0x1.212663dd4a7cfp-1 -18544=-0x1.2bc85e6d90d3p-27 -18546=-0x1.fa7420470078bp-2 -18550=0x1.5e4c409c1c31bp-2 -18551=-0x1.26c37f3df1a47p-6 -18552=0x1.c0b1657694c8dp-3 -18553=0x1.8921b0c06fafap-1 -18554=0x1.7b8477fdef872p-6 -18555=0x1.7e4ee929530fdp-1 -18556=0x1.b2a5e9dd1f1e5p-3 -18557=0x1.2f8bcb4a8449p-1 -18560=0x1.ce5436b1ad0c4p-4 -18561=0x1.15fa77c24546fp-6 -18562=0x1.4fddb73ac3501p-1 -18564=0x1.7d1e5a5c1b049p-1 -18565=-0x1.d4fb831916a58p-3 -18569=0x1.a4cd6a0ea87e1p-2 -18570=0x1.21553b7abfbd3p-3 -18571=-0x1.12d34c6e61b3fp-3 -18601=-0x1.0510123d4c6d1p-9 -18602=-0x1.4685306f0ddd7p-2 -18603=0x1.9081c799d2b3ap-4 -18604=0x1.b4441a98006f9p-7 -18606=-0x1.8c560f14063afp-12 -18607=-0x1.957e4f9534d1dp-1 -18608=0x1.d53242e835f37p-5 -18609=-0x1.a9afdfd9f78dbp-4 -18610=-0x1.b0b6cf5c22384p-3 -18611=0x1.5bdaba67f521ap-8 -18616=0x1.9412010e572d4p-4 -18618=-0x1.6f5c3db977109p-6 -18619=0x1.b160d5aeeb8c9p-6 -18758=0x1.b9601474f8de4p-3 -18760=0x1.07b76a704421p-1 -18761=-0x1.63acb4e17a0cbp-2 -18854=-0x1.576bb7a320fddp-1 -18874=0x1.616ee689bc684p-4 -18903=0x1.b3ed3b3123a5fp+0 -18951=-0x1.b1253a27898c6p-2 -18953=0x1.a188643365e44p-5 -18954=0x1.27c313838b939p-4 -18955=-0x1.3e96b4d1a52a3p-4 -18956=0x1.3112de47ded1dp-12 -18961=0x1.8a560b7f5c89fp-10 -18965=-0x1.eee81b6f5d958p-6 -18966=-0x1.e222086bffc1p-1 -18969=-0x1.386fa966e5ce2p+0 -18970=-0x1.2c9ec41cbb361p-4 -18975=-0x1.bedb8a57700d9p-2 -18976=-0x1.71a51ab35a7bfp-6 -18977=0x1.62e4a58649cb2p-4 -18978=0x1.e15771f60d7bap-4 -18979=-0x1.5afde806baf51p-3 -18981=0x1.3203001ef3b84p-3 -18982=0x1.b0f7f72fd0b76p-7 -18983=-0x1.b012f0890ce5p-2 -18985=0x1.5110e5d102d17p-3 -18986=-0x1.bddb7168ce34fp-4 -18988=-0x1.9f6e8ee111647p-1 -18989=-0x1.7bd034b107778p-2 -18991=-0x1.1ac68792091f2p-22 -18993=-0x1.9ea6bebccfcd4p-3 -18995=0x1.220baff445d0dp-2 -18996=-0x1.f3561bce94b4dp-2 -18999=-0x1.6ca2c324990bbp-2 -19025=-0x1.11536463ed864p-3 -19026=-0x1.2d14c17813c4fp-3 -19027=-0x1.3e6b8cf6336dap-3 -19028=-0x1.abbafce2637adp-5 -19029=0x1.5a1be13ec9a9p-5 -19030=-0x1.6bfbc92c8de45p-4 -19031=0x1.12d6435c59c05p-3 -19032=-0x1.258efe16d6a0cp-3 -19033=-0x1.0dd05e84158a3p-3 -19034=-0x1.159409b91d7aap-2 -19035=-0x1.d5be545be1961p-3 -19036=0x1.2f1f598799f71p-3 -19037=-0x1.421e2927c0bc5p-3 -19039=-0x1.219b9f15d2f2ap-4 -19040=-0x1.435ec2def9992p-1 -19041=-0x1.ef90cae97c45p-2 -19044=-0x1.0f3f6aeee06e9p-1 -19045=-0x1.dee8a89d1b6c6p-3 -19046=-0x1.fce39764e994ap-3 -19048=-0x1.c52f1e56721c8p-4 -19049=-0x1.219972553562fp-3 -19144=0x1.30a7c1b1dcdd7p-1 -19154=-0x1.47738b65f8b68p-1 -19156=-0x1.a7502d4a3a597p-6 -19164=0x1.e73d0cd437912p-2 -19165=-0x1.68d163f8faa51p-2 -19201=-0x1.cd93032268e15p-3 -19275=0x1.16baefd84c4eap-3 -19276=0x1.83176b4d38fe9p-2 -19279=-0x1.a98ae720c2694p-2 -19294=0x1.f86ab0d61dc6bp-4 -19299=0x1.4f633ea03108bp-6 -19328=0x1.eeb32a13353c4p+0 -19375=0x1.338a8d696474p-1 -19376=0x1.bfdbd99967c34p-10 -19383=-0x1.768af37e0eb91p-3 -19386=0x1.c648529a4349ap-3 -19400=-0x1.32c0bf6857379p-6 -19401=0x1.bfba9dc6410a2p-5 -19403=0x1.b524839e55971p-3 -19404=-0x1.9b05b8a8d4cc1p-10 -19406=-0x1.5b71b92efa413p-5 -19408=0x1.e7cf7c546bcc3p-4 -19409=0x1.ea5ba4954776bp-1 -19411=-0x1.07e10156e6219p-10 -19414=0x1.0ad5e8922f862p-1 -19416=0x1.8e7a7ace48e19p-1 -19418=-0x1.1c6b4fb072c47p-2 -19429=-0x1.77ceccf0e1332p-3 -19431=-0x1.9dea6c147b3f9p-6 -19434=0x1.6062b72c6595cp-3 -19441=-0x1.25b9bb30634d9p+0 -19500=-0x1.1a33097f69625p-9 -19501=0x1.438dec3007befp-4 -19503=-0x1.dac20bcf1576dp-6 -19504=0x1.312d2734873ebp-2 -19506=0x1.070df6913c91bp-1 -19511=-0x1.6621ba374b71bp-6 -19514=0x1.7b09319e027bfp-2 -19519=0x1.408eeb5e51997p-6 -19525=-0x1.7c6e40bd4d193p-10 -19526=0x1.3f5171673a494p-4 -19527=0x1.693df17c4cec6p-26 -19529=0x1.323a630407477p-2 -19531=0x1.0083e89d526a1p-1 -19536=-0x1.da86fd177b669p-6 -19539=0x1.f6dbf3f5c9a43p-2 -19544=0x1.659ea9f81c54fp-4 -19550=0x1.309132322098p-5 -19551=0x1.a5fbc8f7cb538p-2 -19552=0x1.beabb42aa1dd7p+0 -19553=-0x1.ef35cd1053e9p-1 -19554=-0x1.c7e3afa906b6p-3 -19556=-0x1.24ba9853493afp-1 -19558=-0x1.3be96f07001e7p-2 -19559=0x1.eeffb743dfd63p-1 -19560=-0x1.92220bfc04a85p-1 -19561=0x1.3a4bedc15160fp-5 -19564=0x1.73b4b2ef9163ap+0 -19565=0x1.45466042cd8ccp-1 -19566=0x1.6fd201216703ep-3 -19569=0x1.2419544032d9cp-1 -19651=-0x1.3bbc2ebf3c2dcp-3 -19653=0x1.a3f6319107888p-1 -19655=0x1.4493b5cacdeafp-1 -19656=-0x1.627b8a9e70aafp-2 -19661=-0x1.4ffc05de7ca1p-2 -19778=0x1.f40799753bb86p-1 -19790=-0x1.a7e8816bcc10dp-3 -19880=0x1.070e4cadd1d26p+0 -19926=-0x1.002d0cef3340fp-1 -19928=0x1.020a35d1f1766p+0 -19929=-0x1.de19d635db5e2p-1 -19930=0x1.7337c0d695fe4p+0 -19931=-0x1.82c7df338e4b7p-1 -19932=0x1.1467510e467efp-1 -19934=0x1.14609405ed59bp-2 -19935=0x1.0043fedeaea75p-1 -19936=-0x1.7d4307a39331fp-1 -19940=-0x1.27eb3555cc1fcp-1 -19947=0x1.3bae889a61b47p+0 -19950=0x1.08f4035493a56p-3 -19951=0x1.972a3f816a09p-5 -19952=0x1.2229ffe43521p-5 -19953=-0x1.0ab1f5e96dcfp-2 -19954=0x1.eb1be12197418p-5 -19955=0x1.73946b471c7e5p-3 -19956=-0x1.d03034ca40e5fp-7 -19957=-0x1.dd44110f0d9c1p-7 -19958=0x1.a66eb8cc0af6bp-4 -19959=-0x1.78102d4c104c3p-2 -19960=-0x1.8135009277aa9p-1 -19961=0x1.511b20ef2ccffp-7 -19963=-0x1.e25afaec4d585p-3 -19965=-0x1.8bb84620944d2p-2 -19966=0x1.ffbd43fa53713p-6 -19968=-0x1.62d2c11463639p-20 -19969=0x1.1fa9e2504273cp-5 -19971=0x1.32126b2fa95dp-3 -19975=-0x1.8a153ebbed45bp-2 -19976=-0x1.5ccfff0b9cef3p-2 -19977=-0x1.2d59367d1861p+0 -19978=0x1.dda9a82a188aap-2 -19979=-0x1.ea35b752e2d9ap-6 -19981=-0x1.9ccdc19396503p-3 -19983=-0x1.0a0450f6d19adp-5 -19984=-0x1.47d9e95b96704p+0 -19985=0x1.64d656463c394p-3 -19986=0x1.189ca78669cf3p-4 -19988=-0x1.09d9f9d0c9c89p-1 -19989=-0x1.17dc6e4f8190cp-1 -19990=-0x1.bb6ffd140ae0fp-3 -19991=-0x1.e638285b6129p-3 -19993=-0x1.f9803b800b763p-2 -19994=-0x1.0fc4c03d17dc1p-2 -19996=-0x1.4e84433ce6f96p-2 -19999=-0x1.b4647d34f0c74p-1 -20053=0x1.65fffa56dc86ep-1 -20054=0x1.b3fafb5b8adbdp-2 -20140=0x1.b77f60377dfa6p-2 -20201=-0x1.efe099b69468ep+0 -20203=0x1.aee5d7a2ca60fp+1 -20209=0x1.68d07ee3041e4p+1 -20279=0x1.0f5d5c0023047p+0 -20325=0x1.5800a1f482665p-1 -20329=-0x1.a3eed160cbaaap-1 -20330=0x1.6b29a330b7c3bp-2 -20404=0x1.04cfa2dee9ce2p-3 -20406=-0x1.05ab8f43d97a2p-1 -20411=0x1.491077c3e71acp-9 -20425=0x1.5800a1f482665p-1 -20429=-0x1.a3eed160cbaaap-1 -20430=0x1.6b29a330b7c3bp-2 -20450=0x1.5800a1f482665p-1 -20454=-0x1.a3eed160cbaaap-1 -20455=0x1.6b29a330b7c3bp-2 -20475=-0x1.cbf542ff90896p-5 -20476=-0x1.797680b795a15p-20 -20479=0x1.fab999a38081ap-5 -20480=0x1.0ec3c99a81145p-14 -20481=0x1.c6de927e984b7p-5 -20483=-0x1.5ad126bdb905ep-1 -20484=-0x1.3290c6a41d9c7p+1 -20485=-0x1.d890c225d163ep-2 -20486=0x1.9d28674d8987fp-7 -20488=-0x1.d12fcb11befaap-5 -20489=0x1.ac22f40a2a1d5p-5 -20490=-0x1.662778a632663p-2 -20491=-0x1.fd9d2ea69bf74p-2 -20493=-0x1.4aa8ac5bff05fp-2 -20496=0x1.d3a1e3c424deep-3 -20499=-0x1.460864dedc834p-5 -20529=0x1.214e3fd3b8b8ap-2 -20536=-0x1.7727377669992p+0 -20611=0x1.dc59c86a4f636p-3 -20679=0x1.2907f2b14cf0ep-3 -20701=0x1.a4b636dfb542bp-1 -20778=0x1.8bd00af04d151p-5 -20779=0x1.f2eaec7a19841p-26 -20801=0x1.05d4daeee218fp-3 -20950=-0x1.6fe70a400e5a8p-3 -20951=-0x1.b1dc310f6fad1p-2 -20953=-0x1.f1ed3c1e6446dp-1 -20954=0x1.34c6f4c723154p-4 -20955=-0x1.2bd5d96b3b298p-1 -20956=-0x1.12578c7af9a0bp-4 -20957=-0x1.4179b681fb239p-2 -20958=-0x1.bfcaa81682653p-2 -20960=-0x1.a0bb67e8a0651p-3 -20961=0x1.0c65a937fde1ep-6 -20964=-0x1.3a8efc32b4802p-2 -20965=0x1.8254d38aa112ep-17 -20966=-0x1.6a4dc6a19c896p-1 -20968=-0x1.0455addee601fp-8 -20969=-0x1.115e50765e134p-2 -20970=-0x1.6b0c536790c67p-2 -20974=-0x1.8bcfd6d999559p-3 -20979=0x1.695c85b420dd1p-6 -20986=0x1.6eb8a2f118bc3p-9 -21026=-0x1.42e17b2748d85p-1 -21201=-0x1.e178775837d2fp-3 -21478=-0x1.92a07507cdcfbp-3 -21479=0x1.c8eacfdaa337ep-10 -21483=0x1.4c876787207a3p-2 -21486=0x1.cec81be83f977p-10 -21489=0x1.1d2c1dbce01d4p-2 -21490=-0x1.b1ac167d9cd7ap-2 -21491=0x1.2356d8547684ep-3 -21576=-0x1.c00c4e643f568p-24 -21578=-0x1.abe5449d2f0d4p-2 -21601=0x1.48a83820a2e5p-2 -21604=-0x1.d3a9f8fde1935p-17 -21610=0x1.01b187053c41fp-3 -21628=0x1.defecb1296ccap-3 -21644=0x1.52f7d43755647p-1 -21800=0x1.4aa8d38cfc1fep-1 -21801=-0x1.2a8ea9cc22d6cp-4 -21802=0x1.0aafbed65d057p-1 -21803=-0x1.0756cb3f5a392p-3 -21804=-0x1.1fe8e39c8897ap-9 -21809=0x1.6e2a30ec09fdap-4 -21810=0x1.5546400db9941p-1 -21811=0x1.6ba8fc65e7039p-11 -21814=-0x1.7f3684c9ee203p-4 -21826=-0x1.04528d6fb5c4bp+0 -21927=-0x1.c63f44b7d1f8dp-3 -21928=-0x1.a03d564762cebp-6 -21929=-0x1.b6c9d8267f21p-11 -21975=0x1.a7ca98d922a0ap-4 -21976=0x1.e5b8961791ad8p-5 -21977=0x1.3f407e6e3976cp-2 -21978=-0x1.37a315969458bp-3 -21979=-0x1.320e640f3c7a5p-4 -21980=-0x1.7c8ad6935414ep-26 -21981=0x1.3680e7ce528dfp-4 -21982=0x1.19bf5b47f33e9p-9 -21983=0x1.403275d677be6p-7 -21986=-0x1.c395959092e91p-11 -21988=0x1.986a6cb85e0d5p-4 -21994=0x1.72f08ccd01662p-3 -22126=-0x1.502f216ae4253p-22 -22129=-0x1.bcd52a6a546f1p-10 -22131=-0x1.27b1a26448682p-1 -22133=0x1.432b6331f4579p-27 -22135=0x1.c069821cf4146p-2 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SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 0 0 [,,] 4 1 0 1 0 0 1 +[1, 2, [1, [ [1 [1, [1, BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 0 0 [,,,] 5 2 0 1 0 0 1 +[1, 2, [1, [ [1 [1, [1, BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 0 0 [,,,] 5 2 0 1 0 0 1 +Text encoder text T Te Tex Text BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 0 0 no 0 2 0 1 0 0 1 +CLIP ViT-L clip C CL CLI CLIP BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 1 0 0 0 0 0 0 0 ---- 4 10 0 1 0 0 1 +Context dim. context C Co Con Cont BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 0 0 . 1 2 0 1 0 0 1 +2048 2048 2048 2 20 204 2048 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 0 0 no 0 0 0 1 0 0 1 +768 768 768 7 76 768 768 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 0 0 no 0 0 0 1 0 0 1 +1024 1024 1024 1 10 102 1024 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 0 0 no 0 0 0 1 0 0 1 +Pooled text pooled P Po Poo Pool BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 0 0 . 1 2 0 1 0 0 1 +OpenCLIP ViT-bigG openclip O Op Ope Open BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 0 0 - 1 3 0 1 0 0 1 +N/A N/A n/a N N/ N/A N/A BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 0 0 / 1 0 0 1 0 0 1 +N/A N/A n/a N N/ N/A N/A BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 0 0 / 1 0 0 1 0 0 1 +of foundational of o of of of BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 1 [,,],: 6 9 0 0 0 0 1 +self-attention and self-attention s se sel self BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 1 -[],---[], 10 10 0 0 0 0 1 +to pure to t to to to BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 1 -[]. 4 4 0 0 0 0 1 +We follow we W We We We BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 2 ,.[],- 6 9 1 0 0 0 1 +putation to putation p pu put puta BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 2 -., 3 9 1 0 0 0 1 +Diffusion architecture, diffusion D Di Dif Diff BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 2 ,: 2 9 1 0 0 0 1 +For efficiency for F Fo For For BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 2 ,, 2 9 1 0 0 0 1 +blocks at blocks b bl blo bloc BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 2 ,() 3 9 1 0 0 0 1 +-see Tab. -see - -s -se -see BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 2 -.... 5 9 1 0 0 0 1 +We opt we W We We We BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 2 -., 3 10 1 0 0 0 1 +we use we w we we we BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 2 -[]-[], 7 9 1 0 0 0 1 +penultimate text penultimate p pe pen penu BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 2 -[].- 5 10 1 0 0 0 1 +condition the condition c co con cond BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 2 -,[] 4 9 1 0 0 0 1 +pooled text pooled p po poo pool BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 2 .. 2 9 1 0 0 0 1 +parameters in parameters p pa par para BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 2 ,... 4 9 1 0 0 0 1 +2.2 Micro-Conditioning 2.2 2 2. 2.2 2.2 BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 1 5 .- 2 10 1 0 0 0 1 +Figure 2: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 5 : 1 1 1 0 0 0 1 +Height-vs-Width distribution height-vs-width H He Hei Heig BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 1 5 -- 2 6 1 0 0 0 1 +pre-training dataset. pre-training p pr pre pre- BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 5 -.- 3 8 1 0 0 0 1 +conditioning, 39% conditioning, c co con cond BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 5 , 1 9 1 0 0 0 1 +to edge to t to to to BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 5 no 0 9 1 0 0 0 1 +by the by b by by by BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 5 .- 2 10 1 0 0 0 1 +alized cell alized a al ali aliz BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 5 . 1 9 1 0 0 0 1 +Conditioning the conditioning C Co Con Cond BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 6 - 1 4 0 0 0 0 1 +torious shortcoming torious t to tor tori BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 6 [] 2 4 0 0 0 0 1 +the fact the t th the the BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 no 0 4 0 0 0 0 1 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1 +can lead can c ca can can BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 no 0 4 0 0 0 0 1 +data being data d da dat data BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 , 1 4 0 0 0 0 1 +loss in loss l lo los loss BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 . 1 4 0 0 0 0 1 +visualize such visualize v vi vis visu BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 . 1 5 0 0 0 0 1 +which SDXL which w wh whi whic BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 . 1 4 0 0 0 0 1 +choice of choice c ch cho choi BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 , 1 4 0 0 0 0 1 +pretraining resolution pretraining p pr pre pret BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 6 no 0 4 0 0 0 0 1 +to a to t to to to BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 6 .,, 3 9 0 0 0 0 1 +upscaling artifacts upscaling u up ups upsc BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 6 ,,,. 4 10 0 0 0 0 1 +Instead, we instead, I In Ins Inst BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 9 ,, 2 9 1 1 0 0 1 +available during available a av ava avai BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 9 .,(..,) 7 9 1 1 0 0 1 +and width and a an and and BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 9 (,). 4 10 1 1 0 0 1 +Each component each E Ea Eac Each BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 9 , 1 9 1 1 0 0 1 +are concatenated are a ar are are BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 9 no 0 9 1 1 0 0 1 +embedding [5]. embedding e em emb embe BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 9 []. 3 1 1 1 0 0 1 +At inference at A At At At BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 11 ,- 2 9 0 1 0 0 1 +conditioning. Evidently conditioning. c co con cond BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 11 .(.), 5 10 0 1 0 0 1 +3 3 3 3 3 3 3 BLOCKSTART PAGEEND SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 1 11 no 0 10 0 1 0 0 1 +c size c c c c c BLOCKSTART PAGESTART NEWFONT LOWERFONT 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 1 0 (,) 3 10 1 1 0 0 1 +c size c c c c c BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 1 0 (,), 4 10 1 1 0 0 1 +c size c c c c c BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 1 0 (,), 4 10 1 1 0 0 1 +c size c c c c c BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 1 0 (,), 4 10 1 1 0 0 1 +'A robot 'a ' 'A 'A 'A BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 1 0 '.,.' 5 10 1 0 0 0 1 +'Panda mad 'panda ' 'P 'Pa 'Pan BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 1 1 ',.' 4 10 1 0 0 0 1 +Figure 3: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 1 1 :-: 3 9 1 0 0 0 1 +SDXL and sdxl S SD SDX SDXL BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 1 1 -. 2 9 1 0 0 0 1 +conditioning on conditioning c co con cond BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 1 .,...:, 7 10 1 0 0 0 1 +use the use u us use use BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 1 (..), 5 10 1 0 0 0 1 +before 1024 before b be bef befo BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 1 1 .. 2 4 1 0 0 0 1 +resolution-dependent image resolution-dependent r re res reso BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 -, 2 9 1 0 0 0 1 +corresponding to corresponding c co cor corr BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 .., 3 9 1 0 0 0 1 +generated by generated g ge gen gene BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 (..), 5 9 1 0 0 0 1 +are less are a ar are are BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 -() 3 10 1 0 0 0 1 +SDXL model. sdxl S SD SDX SDXL BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 2 3 . 1 1 1 0 0 0 1 +Table 2: table T Ta Tab Tabl BLOCKSTART PAGEIN SAMEFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 4 : 1 10 0 0 0 0 1 +size of size s si siz size BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 4 - 1 9 0 0 0 0 1 +formance on formance f fo for form BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 2 4 -[] 3 9 0 0 0 0 1 +on 512 on o on on on BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 4 . 1 4 0 0 0 0 1 +model model model m mo mod mode BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 no 0 3 0 0 0 0 1 +FID-5k ↓ fid-5k F FI FID FID- BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 -- 2 10 0 0 0 0 1 +CIN-512-only CIN-512-only cin-512-only C CI CIN CIN- BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 -- 2 9 0 0 0 0 1 +43.84 43.84 43.84 4 43 43. 43.8 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 . 1 4 0 0 0 0 1 +110.64 110.64 110.64 1 11 110 110. BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 . 1 5 0 0 0 0 1 +CIN-nocond CIN-nocond cin-nocond C CI CIN CIN- BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 2 5 - 1 7 0 0 0 0 1 +39.76 39.76 39.76 3 39 39. 39.7 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 . 1 4 0 0 0 0 1 +211.50 211.50 211.50 2 21 211 211. BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 . 1 5 0 0 0 0 1 +CIN-size-cond CIN-size-cond cin-size-cond C CI CIN CIN- BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 2 5 -- 2 10 0 0 0 0 1 +36.53 36.53 36.53 3 36 36. 36.5 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 . 1 4 0 0 0 0 1 +215.34 215.34 215.34 2 21 215 215. BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 . 1 5 0 0 0 0 1 +We quantitatively we W We We We BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 5 - 1 5 0 0 0 0 1 +fective conditioning fective f fe fec fect BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 2 5 no 0 5 0 0 0 0 1 +three LDMs three t th thr thre BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 [] 2 5 0 0 0 0 1 +size 512 size s si siz size BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 :(--) 5 5 0 0 0 0 1 +all training all a al all all BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 no 0 5 0 0 0 0 1 +512 pixels 512 5 51 512 512 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 2 5 - 1 5 0 0 0 0 1 +ages. For ages. a ag age ages BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 .- 2 5 0 0 0 0 1 +without size without w wi wit with BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 . 1 5 0 0 0 0 1 +only used only o on onl only BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 --. 3 5 0 0 0 0 1 +5k samples 5k 5 5k 5k 5k BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 5 [](-) 5 5 0 0 0 0 1 +guidance scale guidance g gu gui guid BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 [][][](- 8 9 0 0 0 0 1 +idation set). idation i id ida idat BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 2 5 ).--(,). 8 9 0 0 0 0 1 +Tab. 2 tab. T Ta Tab Tab. BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 5 .-- 3 9 0 0 0 0 1 +both metrics. both b bo bot both BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 .-- 3 9 0 0 0 0 1 +overfitting on overfitting o ov ove over BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 2 5 no 0 10 0 0 0 0 1 +distribution of distribution d di dis dist BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 -., 3 10 0 0 0 0 1 +quantitative scores quantitative q qu qua quan BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 (--) 4 10 0 0 0 0 1 +DMs [40, dms D DM DMs DMs BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 2 5 [,,](.), 8 9 0 0 0 0 1 +of FID of o of of of BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 5 . 1 5 0 0 0 0 1 +Conditioning the conditioning C Co Con Cond BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 10 . 1 9 0 1 0 0 1 +failure mode failure f fa fai fail BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 10 :,- 3 9 0 1 0 0 1 +the cat the t th the the BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 10 --. 3 10 0 1 0 0 1 +use of use u us use use BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 10 : 1 9 0 1 0 0 1 +4 4 4 4 4 4 4 BLOCKSTART PAGEEND NEWFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 2 11 no 0 10 0 1 0 0 1 +'A propaganda 'a ' 'A 'A 'A BLOCKSTART PAGESTART NEWFONT LOWERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 2 0 ' 1 10 1 1 0 0 1 +emperor napoleon emperor e em emp empe BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 0 .' 2 8 1 1 0 0 1 +'a close-up 'a ' 'a 'a 'a BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 2 0 '-, 3 10 1 1 0 0 1 +cinematic shot.' cinematic c ci cin cine BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 2 0 .' 2 4 1 1 0 0 1 +SD 1-5 sd S SD SD SD BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 2 0 - 1 10 1 1 0 0 1 +SD 2-1 sd S SD SD SD BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 2 0 - 1 10 1 0 0 0 1 +SDXL SDXL sdxl S SD SDX SDXL BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 2 0 no 0 10 1 0 0 0 1 +Figure 4: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 0 :., 3 9 1 0 0 0 1 +show 3 show s sh sho show BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 0 []-.[]. 7 10 1 0 0 0 1 +Additional samples additional A Ad Add Addi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 0 .. 2 2 1 0 0 0 1 +PyTorch [32] pytorch P Py PyT PyTo BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 2 1 [],() 5 10 1 0 0 0 1 +such that such s su suc such BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 1 ,() 3 9 1 0 0 0 1 +image along image i im ima imag BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 1 ., 2 9 1 0 0 0 1 +leak into leak l le lea leak BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 1 0 0 0 0 0 2 1 ,. 2 7 1 0 0 0 1 +To fix to T To To To BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 3 ,:, 3 9 0 0 0 0 1 +we uniformly we w we we we BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 ( 1 10 0 0 0 0 1 +from the from f fr fro from BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 -,) 3 9 0 0 0 0 1 +as conditioning as a as as as BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 , 1 9 0 0 0 0 1 +above. The above. a ab abo abov BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 .. 2 9 0 0 0 0 1 +We emphasize we W We We We BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 3 . 1 9 0 0 0 0 1 +crop-and size-conditioning crop-and c cr cro crop BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 --., 4 9 0 0 0 0 1 +embedding along embedding e em emb embe BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 3 ,. 2 9 0 0 0 0 1 +Alg. 1 alg. A Al Alg Alg. BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 2 3 .. 2 9 0 0 0 0 1 +Given that given G Gi Giv Give BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 2 6 ,,-,(,) 7 10 0 0 0 0 1 +(0, 0) (0, ( (0 (0, (0, BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 2 6 (,)-. 5 8 0 0 0 0 1 +See Fig. see S Se See See BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 1 0 0 0 0 0 2 6 .:(,), 6 10 0 0 0 0 1 +cropping during cropping c cr cro crop BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 6 .-, 3 9 0 0 0 0 1 +forms with forms f fo for form BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 2 6 [],[]. 6 8 0 0 0 0 1 +While other while W Wh Whi Whil BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 3 8 [], 3 10 0 0 0 0 1 +cropping-induced data cropping-induced c cr cro crop BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 8 -, 2 9 0 0 0 0 1 +process -we process p pr pro proc BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 8 -. 2 9 0 0 0 0 1 +Furthermore, it furthermore, F Fu Fur Furt BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 3 8 ,, 2 10 0 0 0 0 1 +additional data additional a ad add addi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 8 . 1 3 0 0 0 0 1 +2.3 Multi-Aspect 2.3 2 2. 2.3 2.3 BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 3 9 .- 2 10 0 1 0 0 1 +Real-world datasets real-world R Re Rea Real BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 3 9 --(...) 7 9 0 1 0 0 1 +common output common c co com comm BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 9 -- 2 9 0 1 0 0 1 +pixels, we pixels, p pi pix pixe BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 3 9 ,, 2 10 0 1 0 0 1 +landscape (e.g., 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resize ▷ ▷ ▷ ▷ ▷ BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 3 0 no 0 4 1 0 0 0 1 +if h if i if if if BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 0 no 0 3 1 0 0 0 1 +c left c c c c c BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 3 0 (,()-) 6 3 1 0 0 0 1 +▷ sample ▷ ▷ ▷ ▷ ▷ BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 3 0 no 0 5 1 0 0 0 1 +c top c c c c c BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 3 0 no 0 1 1 0 0 0 1 +else if else e el els else BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 1 0 0 0 0 0 3 0 no 0 4 1 0 0 0 1 +c top c c c c c BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 3 0 (,()-) 6 3 1 0 0 0 1 +▷ sample ▷ ▷ ▷ ▷ ▷ BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 3 0 no 0 5 1 0 0 0 1 +c left c c c c c BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 3 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S Se Sec Sec. BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 3 1 .....- 6 10 0 0 0 0 1 +operation. Note operation. o op ope oper BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 1 .--, 4 10 0 0 0 0 1 +crop-conditioning then crop-conditioning c cr cro crop BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 1 -(). 4 9 0 0 0 0 1 +implementation, however, implementation, i im imp impl BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 1 ,,-. 4 8 0 0 0 0 1 +2.4 Improved 2.4 2 2. 2.4 2.4 BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 3 2 . 1 10 0 0 0 0 1 +Table 3: table T Ta Tab Tabl BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 3 2 : 1 9 0 0 0 0 1 +the COCO2017 the t th the the BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 2 [], 3 9 0 0 0 0 1 +256 × 256 2 25 256 256 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 3 2 .:. 3 9 0 0 0 0 1 +improved version improved i im imp impr BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 2 .', 3 10 0 0 0 0 1 +where the where w wh whe wher BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 2 no 0 9 0 0 0 0 1 +on the on o on on on BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 2 [],. 4 9 0 0 0 0 1 +Note that note N No Not Note BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 3 2 . 1 9 0 0 0 0 1 +model model model m mo mod mode BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 3 3 no 0 2 0 0 0 0 1 +PNSR ↑ pnsr P PN PNS PNSR BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 3 3 no 0 10 0 0 0 0 1 +SDXL-VAE SDXL-VAE sdxl-vae S SD SDX SDXL BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 4 3 - 1 8 0 0 0 0 1 +24.7 24.7 24.7 2 24 24. 24.7 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +0.73 0.73 0.73 0 0. 0.7 0.73 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +0.88 0.88 0.88 0 0. 0.8 0.88 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +4.4 4.4 4.4 4 4. 4.4 4.4 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 3 0 0 0 0 1 +SD-VAE 1.x sd-vae S SD SD- SD-V BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 4 3 -. 2 10 0 0 0 0 1 +23.4 23.4 23.4 2 23 23. 23.4 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +0.69 0.69 0.69 0 0. 0.6 0.69 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +0.96 0.96 0.96 0 0. 0.9 0.96 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +5.0 5.0 5.0 5 5. 5.0 5.0 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 3 0 0 0 0 1 +SD-VAE 2.x sd-vae S SD SD- SD-V BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 4 3 -. 2 10 0 0 0 0 1 +24.5 24.5 24.5 2 24 24. 24.5 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +0.71 0.71 0.71 0 0. 0.7 0.71 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +0.92 0.92 0.92 0 0. 0.9 0.92 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 4 0 0 0 0 1 +4.7 4.7 4.7 4 4. 4.7 4.7 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 . 1 3 0 0 0 0 1 +Stable Diffusion stable S St Sta Stab BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 4 ,- 2 4 0 0 0 0 1 +trained, learned trained, t tr tra trai BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 4 ,() 3 4 0 0 0 0 1 +autoencoder. 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The average. a av ave aver BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 4 . 1 10 0 0 0 0 1 +metrics, see metrics, m me met metr BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 4 4 ,... 4 7 0 0 0 0 1 +2.5 Putting 2.5 2 2. 2.5 2.5 BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 5 . 1 10 0 0 0 0 1 +We train we W We We We BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 5 ,,-... 6 9 0 0 0 0 1 +and a and a an and and BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 5 -[,]., 6 9 0 0 0 0 1 +(see Tab. (see ( (s (se (see BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 4 5 (.)--. 6 9 0 0 0 0 1 +600 000 600 6 60 600 600 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 4 5 -,- 3 9 0 0 0 0 1 +and crop-conditioning and a an and and BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 5 -... 4 9 0 0 0 0 1 +another 200 another a an ano anot BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 5 ,-(..) 6 10 0 0 0 0 1 +with an with w wi wit with BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 5 -[,].(.., 9 9 0 0 0 0 1 +App. I) app. A Ap App App. BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 4 5 .). 3 3 0 0 0 0 1 +Refinement Stage refinement R Re Ref Refi BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 7 , 1 9 0 0 0 0 1 +local quality, local l lo loc loca BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 7 ,..,, 5 10 0 0 0 0 1 +which is which w wh whi whic BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 7 -,- 3 9 0 0 0 0 1 +introduced by introduced i in int intr BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 7 [].[] 5 9 0 0 0 0 1 +refinement model refinement r re ref refi BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 7 ()., 4 9 0 0 0 0 1 +the base the t th the the BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 7 ,( 2 9 0 0 0 0 1 +Fig. 1), fig. F Fi Fig Fig. BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 7 .),., 5 10 0 0 0 0 1 +detailed backgrounds detailed d de det deta BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 7 ,... 4 7 0 0 0 0 1 +To assess to T To To To BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 9 (), 3 9 0 1 0 0 1 +study, and study, s st stu stud BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 9 ,:, 3 9 0 1 0 0 1 +(with refiner), (with ( (w (wi (wit BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 4 9 (),... 6 10 0 1 0 0 1 +the refinement the t th the the BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 9 ,.. 3 9 0 1 0 0 1 +significant margin significant s si sig sign BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 9 (:/:.,:., 9 9 0 1 0 0 1 +1.5: 7.91%, 1.5: 1 1. 1.5 1.5: BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 9 .:.,.:.).., 11 9 0 1 0 0 1 +pipeline. However, pipeline. p pi pip pipe BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 9 ., 2 9 0 1 0 0 1 +improvements of improvements i im imp impr BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 9 . 1 9 0 1 0 0 1 +App. F. app. A Ap App App. BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 4 9 ...[]. 6 8 0 1 0 0 1 +7 7 7 7 7 7 7 BLOCKSTART PAGEEND SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 4 11 no 0 10 0 1 0 0 1 +Figure 6: figure F Fi Fig Figu BLOCKSTART PAGESTART SAMEFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 0 :(-)()() 8 8 1 1 0 0 1 +discussed. Prompt: discussed. d di dis disc BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 0 .:" 3 9 1 1 0 0 1 +buildings and buildings b bu bui buil BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 0 ,,,,,".. 8 10 1 1 0 0 1 +for additional for f fo for for BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 0 . 1 2 1 1 0 0 1 +3 Future 3 3 3 3 3 BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 4 1 no 0 10 1 1 0 0 1 +This report this T Th Thi This BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 1 no 0 10 1 1 0 0 1 +for text-to-image for f fo for for BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 1 --., 4 10 1 1 0 0 1 +prompt adherence prompt p pr pro prom BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 1 ,, 2 9 1 1 0 0 1 +the model the t th the the BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 1 : 1 3 1 1 0 0 1 +• Single • • • • • BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 4 3 •:,- 4 9 0 0 0 0 1 +with an with w wi wit with BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 . 1 9 0 0 0 0 1 +memory, hampering memory, m me mem memo BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 ,. 2 9 0 0 0 0 1 +to provide to t to to to BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 . 1 5 0 0 0 0 1 +• Text • • • • • BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 4 3 •:(-[]) 7 8 0 0 0 0 1 +help to help h he hel help BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 , 1 9 0 0 0 0 1 +incorporating byte-level incorporating i in inc inco BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 -[,][, 6 9 0 0 0 0 1 +40] may 40] 4 40 40] 40] BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 ]. 2 4 0 0 0 0 1 +• Architecture: • • • • • BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 4 3 •:, 3 9 0 0 0 0 1 +transformer-based architectures transformer-based t tr tra tran BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 -[][], 6 8 0 0 0 0 1 +benefit. We benefit. b be ben bene BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 .,, 3 9 0 0 0 0 1 +enable scaling enable e en ena enab BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 -. 2 6 0 0 0 0 1 +• Distillation: • • • • • BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 4 3 •:, 3 10 0 0 0 0 1 +they come they t th the they BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 (). 3 8 0 0 0 0 1 +Future work future F Fu Fut Futu BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 4 3 , 1 9 0 0 0 0 1 +sampling speed, sampling s sa sam samp BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 ,-[],-[,,] 10 9 0 0 0 0 1 +distillation [41, distillation d di dis dist BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 [,,]. 5 2 0 0 0 0 1 +• Our • • • • • BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 4 3 •-[],-[, 8 9 0 0 0 0 1 +25] for 25] 2 25 25] 25] BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 4 3 ].-.[] 6 8 0 0 0 0 1 +promising candidate promising p pr pro prom BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 , 1 9 0 0 0 0 1 +for increased for f fo for for BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 4 3 -. 2 8 0 0 0 0 1 +8 8 8 8 8 8 8 BLOCKEND PAGEEND SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 4 3 no 0 0 0 0 0 0 1 +Appendix Appendix appendix A Ap App Appe BLOCKSTART PAGESTART NEWFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 0 no 0 10 0 0 0 0 1 +A Acknowledgements a A A A A BLOCKSTART PAGEIN SAMEFONT LOWERFONT 0 0 ALLCAP NODIGIT 1 0 1 0 0 0 0 0 5 0 no 0 10 0 0 0 0 1 +We thank we W We We We BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 0 ,,,: 4 10 1 1 0 0 1 +Goodwin, Benjamin goodwin, G Go Goo Good BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 5 0 ,,,,, 5 9 1 1 0 0 1 +Saini, Ian saini, S Sa Sai Sain BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 5 0 ,,,,,,,, 8 9 1 1 0 0 1 +Yannik Marek, yannik Y Ya Yan Yann BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 5 0 ,.. 3 8 1 1 0 0 1 +B Limitations b B B B B BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 5 1 no 0 10 1 1 0 0 1 +'A close 'a ' 'A 'A 'A BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 5 1 ' 1 8 1 1 0 0 1 +with leaves with w wi wit with BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 1 .' 2 10 1 1 0 0 1 +'An empty 'an ' 'A 'An 'An BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 1 '. 2 10 1 1 0 0 1 +The TV the T Th The The BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 1 .' 2 8 1 1 0 0 1 +'A grand 'a ' 'A 'A 'A BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 5 2 '.' 3 10 1 0 0 0 1 +'Three quarters 'three ' 'T 'Th 'Thr BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 2 ' 1 9 1 0 0 0 1 +truck with truck t tr tru truc BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 2 .' 2 10 1 0 0 0 1 +Figure 7: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 2 :, 2 9 1 0 0 0 1 +the model the t th the the BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 2 no 0 9 1 0 0 0 1 +detailed descriptions detailed d de det deta BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 2 (..).,(.. 9 10 1 0 0 0 1 +left) and left) l le lef left BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 2 )(..). 6 9 1 0 0 0 1 +All examples all A Al All All BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 2 []-.[]. 7 9 1 0 0 0 1 +While our while W Wh Whi Whil BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 4 - 1 9 1 0 0 0 1 +sizing complex sizing s si siz sizi BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 4 ,. 2 10 1 0 0 0 1 +limitations is limitations l li lim limi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 4 . 1 9 1 0 0 0 1 +Firstly, the firstly, F Fi Fir Firs BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 5 ,, 2 9 0 0 0 0 1 +hands (see hands h ha han hand BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 5 (.,)., 6 10 0 0 0 0 1 +human anatomy human h hu hum huma BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 5 . 1 9 0 0 0 0 1 +suggests the suggests s su sug sugg BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 5 no 0 9 0 0 0 0 1 +fine-grained details. fine-grained f fi fin fine BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 5 -. 2 9 0 0 0 0 1 +very high very v ve ver very BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 5 no 0 9 0 0 0 0 1 +shape and shape s sh sha shap BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 5 . 1 4 0 0 0 0 1 +Secondly, while secondly, S Se Sec Seco BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 7 ,, 2 9 0 0 0 0 1 +important to important i im imp impo BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 7 ., 2 9 0 0 0 0 1 +lighting effects lighting l li lig ligh BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 7 , 1 10 0 0 0 0 1 +generated images. generated g ge gen gene BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 7 . 1 9 0 0 0 0 1 +model-generated visuals model-generated m mo mod mode BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 7 -. 2 8 0 0 0 0 1 +Furthermore, the furthermore, F Fu Fur Furt BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 5 9 ,'-,- 5 9 0 1 0 0 1 +tently introduce tently t te ten tent BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 9 ., 2 10 0 1 0 0 1 +biases when biases b bi bia bias BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 9 . 1 6 0 1 0 0 1 +In certain in I In In In BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 1 0 0 0 0 0 5 10 ,- 2 9 0 1 0 0 1 +nomenon known nomenon n no nom nome BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 10 "". 3 9 0 1 0 0 1 +distinct visual distinct d di dis dist BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 10 .,.,, 5 9 0 1 0 0 1 +an instance an a an an an BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 1 0 0 0 0 0 5 10 .., 3 10 0 1 0 0 1 +the penguin the t th the the BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 10 """", 5 9 0 1 0 0 1 +9 9 9 9 9 9 9 BLOCKSTART PAGEEND SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 5 11 no 0 10 0 1 0 0 1 +gloves and gloves g gl glo glov BLOCKSTART PAGESTART SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 0 . 1 8 0 1 0 0 1 +model's ability model's m mo mod mode BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 0 '. 2 9 0 1 0 0 1 +root cause root r ro roo root BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 1 0 0 0 0 0 5 0 -:, 3 10 0 1 0 0 1 +information into information i in inf info BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 0 ,, 2 9 0 1 0 0 1 +et al. et e et et et BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 5 0 .[]., 5 9 0 1 0 0 1 +the contrastive the t th the the BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 0 , 1 9 0 1 0 0 1 +needed within needed n ne nee need BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 5 0 []. 3 3 0 1 0 0 1 +Additionally, while additionally, A Ad Add Addi BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 6 4 ,, 2 9 0 1 0 0 1 +it still it i it it it BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 4 ,., 3 9 0 1 0 0 1 +may contain may m ma may may BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 1 0 0 1 0 0 6 4 ,.. 3 9 0 1 0 0 1 +limitation requires limitation l li lim limi BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 4 ' 1 10 0 1 0 0 1 +generation capabilities, generation g ge gen gene BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 4 ,- 2 9 0 1 0 0 1 +et al. et e et et et BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 4 .[],-. 6 9 0 1 0 0 1 +Alternatively, scaling alternatively, A Al Alt Alte BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 6 4 ,[,]. 5 7 0 1 0 0 1 +In conclusion, in I In In In BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 1 0 0 0 0 0 6 9 ,, 2 9 0 1 0 0 1 +certain limitations. certain c ce cer cert BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 9 ., 2 10 0 1 0 0 1 +photorealism, further photorealism, p ph pho phot BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 9 ,,, 3 9 0 1 0 0 1 +highlight avenues highlight h hi hig high BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 9 . 1 5 0 1 0 0 1 +10 10 10 1 10 10 10 BLOCKSTART PAGEEND SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 6 11 no 0 10 0 0 0 0 1 +C Diffusion c C C C C BLOCKSTART PAGESTART NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 6 0 no 0 10 0 1 0 0 1 +In this in I In In In BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 1 1 0 0 0 0 0 6 0 ,.-- 4 8 0 1 0 0 1 +work [47] work w wo wor work BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 0 [].[].() 8 9 0 1 0 0 1 +and let and a an and and BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 0 (;)...-. 8 9 0 1 0 0 1 +sufficiently large sufficiently s su suf suff BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 0 ,(;) 4 7 0 1 0 0 1 +max -variance max m ma max max BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 0 0 0 0 0 0 6 0 -. 2 2 0 1 0 0 1 +Capitalizing on capitalizing C Ca Cap Capi BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 6 0 ,(,) 4 9 0 1 0 0 1 +sequentially denoise sequentially s se seq sequ BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 0 (;),,...,,. 11 10 0 1 0 0 1 +a well-trained a a a a a BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 1 0 0 0 0 0 6 0 -. 2 7 0 1 0 0 1 +Sampling. In sampling. S Sa Sam Samp BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 6 2 ., 2 10 0 1 0 0 1 +the numerical the t th the the BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 2 ()[] 4 9 0 1 0 0 1 +dx = dx d dx dx dx BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 3 -()()(;()), 11 10 0 0 0 0 1 +(1) (1) (1) ( (1 (1) (1) BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 6 3 () 2 1 0 0 0 0 1 +where ∇ where w wh whe wher BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 3 (;)[].():[,]- 13 10 0 0 0 0 1 +σ(t) denotes σ(t) σ σ( σ(t σ(t) BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 3 ()()., 6 9 0 0 0 0 1 +differential equation differential d di dif diff BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 3 ()[,]: 6 3 0 0 0 0 1 +dx = dx d dx dx dx BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 4 -()()(;()) 10 10 0 0 0 0 1 +Probability Flow probability P Pr Pro Prob BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 6 4 ;.() 4 10 0 0 0 0 1 +-β(t)σ 2 -β(t)σ - -β -β( -β(t BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 4 -()()(;())()() 14 10 0 0 0 0 1 +Langevin diffusion langevin L La Lan Lang BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 6 5 no 0 10 0 0 0 0 1 +, (2) , , , , , BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 6 5 ,() 3 10 0 0 0 0 1 +where dω where w wh whe wher BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 5 ., 2 10 0 0 0 0 1 +or the or o or or or BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 5 . 1 6 0 0 0 0 1 +Training. DM training. T Tr Tra Trai BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 6 5 .(;)(;). 8 9 0 0 0 0 1 +The model the T Th The The BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 6 5 ,,(;)(;)((;)- 13 8 0 0 0 0 1 +x)/σ 2 x)/σ x x) x)/ x)/σ BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 5 )/[],,,(), 10 10 0 0 0 0 1 +n ∼ n n n n n BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 6 5 ,,,. 4 9 0 0 0 0 1 +D θ d D D D D BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 6 5 ()() 4 8 0 0 0 0 1 +E (x0,c)∼p e E E E E BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 6 7 (,)(,),(,)(,)(;,)- 18 10 0 0 0 0 1 +2 , 2 2 2 2 2 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 6 7 , 1 0 0 0 0 0 1 +(3) (3) (3) ( (3 (3) (3) BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 6 7 () 2 0 0 0 0 0 1 +where p(σ, where w wh whe wher BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 8 (,)();,,(),: 12 9 0 0 0 0 1 +weighting function, weighting w we wei weig BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 6 8 ,,..,,, 7 10 0 0 0 0 1 +combination thereof. combination c co com comb BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 8 .,() 4 9 0 0 0 0 1 +levels and levels l le lev leve BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 8 -[,,]. 6 6 0 0 0 0 1 +Classifier-free guidance. classifier-free C Cl Cla Clas BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 6 9 -.-[] 5 10 0 1 0 0 1 +process of process p pr pro proc BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 9 no 0 9 0 1 0 0 1 +unconditional model unconditional u un unc unco BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 6 9 no 0 1 0 1 0 0 1 +D w d D D D D BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 6 10 (;,)()(;,)-(;), 15 10 0 1 0 0 1 +(4) (4) (4) ( (4 (4) (4) BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 6 10 () 2 0 0 1 0 0 1 +where w where w wh whe wher BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 10 ., 2 9 0 1 0 0 1 +alongside the alongside a al alo alon BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 10 no 0 9 0 1 0 0 1 +with a with w wi wit with BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 10 .(),..,[].- 11 10 0 1 0 0 1 +to improve to t to to to BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 10 ,,--[,]. 8 8 0 1 0 0 1 +11 11 11 1 11 11 11 BLOCKSTART PAGEEND SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 7 11 no 0 10 0 0 0 0 1 +D Comparison d D D D D BLOCKSTART PAGESTART NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 7 0 no 0 10 1 1 0 0 1 +Figure 8: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 1 :,-,, 5 9 1 0 0 0 1 +v5.2. To v5.2. v v5 v5. v5.2 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 1 ..-,(). 7 9 1 0 0 0 1 +was uniformly was w wa was was BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 1 . 1 10 1 0 0 0 1 +seed-setting feature, seed-setting s se see seed BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 1 -,. 3 5 1 0 0 0 1 +12 12 12 1 12 12 12 BLOCKSTART PAGEEND SAMEFONT HIGHERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 7 11 no 0 10 0 0 0 0 1 +E Comparison e E E E E BLOCKSTART PAGESTART NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 7 0 . 1 10 0 1 0 0 1 +E.1 Overall e.1 E E. E.1 E.1 BLOCKSTART PAGEIN SAMEFONT LOWERFONT 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 10 0 1 0 0 1 +To asses to T To To To BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 -- 2 10 0 1 0 0 1 +image generation image i im ima imag BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 0 . 1 9 0 1 0 0 1 +(P2) benchmark (p2) ( (P (P2 (P2) BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 ()[],--- 8 9 0 1 0 0 1 +ing prompts. ing i in ing ing BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 0 0 0 0 0 0 7 0 . 1 1 0 1 0 0 1 +For our for F Fo For For BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 1 ,, 2 8 0 1 0 0 1 +images by images i im ima imag BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 1 (.,). 5 8 0 1 0 0 1 +were then were w we wer were BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 1 ,. 2 9 0 1 0 0 1 +The results the T Th The The BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 1 .., 3 10 0 1 0 0 1 +Midjourney in midjourney M Mi Mid Midj BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 7 1 . 1 3 0 1 0 0 1 +Vanilla Vanilla vanilla V Va Van Vani BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 4 no 0 10 0 0 0 0 1 +0.0 0.0 0.0 0 0. 0.0 0.0 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.1 0.1 0.1 0 0. 0.1 0.1 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.2 0.2 0.2 0 0. 0.2 0.2 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.3 0.3 0.3 0 0. 0.3 0.3 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.4 0.4 0.4 0 0. 0.4 0.4 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.5 0.5 0.5 0 0. 0.5 0.5 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.6 0.6 0.6 0 0. 0.6 0.6 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.7 0.7 0.7 0 0. 0.7 0.7 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.8 0.8 0.8 0 0. 0.8 0.8 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +0.9 0.9 0.9 0 0. 0.9 0.9 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +1.0 1.0 1.0 1 1. 1.0 1.0 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 3 0 0 0 0 1 +Frequency → frequency F Fr Fre Freq BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 4 no 0 10 0 0 0 0 1 +Figure 9: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 4 :,.., 5 9 0 0 0 0 1 +was the was w wa was was BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 ."""" 5 9 0 0 0 0 1 +PartiPrompts (P2) partiprompts P Pa Par Part BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 7 4 ().,... 7 9 0 0 0 0 1 +testing indicates testing t te tes test BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 1 0 0 0 0 0 7 4 -., 3 10 0 0 0 0 1 +but the but b bu but but BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 . 1 9 0 0 0 0 1 +E.2 Category e.2 E E. E.2 E.2 BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 7 .() 3 10 0 0 0 0 1 +Each prompt each E Ea Eac Each BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 7 , 1 9 0 0 0 0 1 +different difficult different d di dif diff BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 7 . 1 9 0 0 0 0 1 +(Fig. 10) (fig. ( (F (Fi (Fig BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 7 7 (.)(.). 7 9 0 0 0 0 1 +Midjourney, and midjourney, M Mi Mid Midj BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 7 7 , 1 10 0 0 0 0 1 +or SDXL or o or or or BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 7 . 1 3 0 0 0 0 1 +Food & food F Fo Foo Food BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 9 no 0 10 0 0 0 0 1 +Animals Animals animals A An Ani Anim BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 9 no 0 10 0 0 0 0 1 +Artifacts Artifacts artifacts A Ar Art Arti BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 7 9 no 0 10 0 0 0 0 1 +Arts Arts arts A Ar Art Arts BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 9 no 0 10 0 0 0 0 1 +Illustrations Illustrations illustrations I Il Ill Illu BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 9 no 0 10 0 0 0 0 1 +Abstract Abstract abstract A Ab Abs Abst BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 9 no 0 10 0 0 0 0 1 +0.0 0.0 0.0 0 0. 0.0 0.0 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.1 0.1 0.1 0 0. 0.1 0.1 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.2 0.2 0.2 0 0. 0.2 0.2 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.3 0.3 0.3 0 0. 0.3 0.3 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.4 0.4 0.4 0 0. 0.4 0.4 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.5 0.5 0.5 0 0. 0.5 0.5 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.6 0.6 0.6 0 0. 0.6 0.6 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.7 0.7 0.7 0 0. 0.7 0.7 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.8 0.8 0.8 0 0. 0.8 0.8 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +0.9 0.9 0.9 0 0. 0.9 0.9 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +1.0 1.0 1.0 1 1. 1.0 1.0 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 9 . 1 3 0 0 0 0 1 +Frequency → frequency F Fr Fre Freq BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 9 no 0 10 0 0 0 0 1 +Figure 10: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 10 :(). 4 10 0 0 0 0 1 +particular text particular p pa par part BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 10 ... 3 8 0 0 0 0 1 +1 We 1 1 1 1 1 BLOCKSTART PAGEIN SAMEFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 7 11 .. 2 10 0 1 0 0 1 +13 13 13 1 13 13 13 BLOCKSTART PAGEEND SAMEFONT HIGHERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 7 11 no 0 10 0 1 0 0 1 +Imagination Imagination imagination I Im Ima Imag BLOCKSTART PAGESTART NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 1 0 0 1 +Writing & writing W Wr Wri Writ BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 1 0 0 1 +Quantity Quantity quantity Q Qu Qua Quan BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 1 0 0 1 +Complex Complex complex C Co Com Comp BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 1 0 0 1 +Fine-grained Detail fine-grained F Fi Fin Fine BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 7 0 - 1 10 0 1 0 0 1 +Perspective Perspective perspective P Pe Per Pers BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 1 0 0 1 +Style & style S St Sty Styl BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 0 0 0 1 +Simple Detail simple S Si Sim Simp BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 0 0 0 1 +Linguistic Structures linguistic L Li Lin Ling BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 0 0 0 0 1 +Properties & properties P Pr Pro Prop BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 1 0 0 0 1 +0.0 0.0 0.0 0 0. 0.0 0.0 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.1 0.1 0.1 0 0. 0.1 0.1 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.2 0.2 0.2 0 0. 0.2 0.2 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.3 0.3 0.3 0 0. 0.3 0.3 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.4 0.4 0.4 0 0. 0.4 0.4 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.5 0.5 0.5 0 0. 0.5 0.5 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.6 0.6 0.6 0 0. 0.6 0.6 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.7 0.7 0.7 0 0. 0.7 0.7 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.8 0.8 0.8 0 0. 0.8 0.8 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +0.9 0.9 0.9 0 0. 0.9 0.9 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +1.0 1.0 1.0 1 1. 1.0 1.0 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 0 . 1 3 1 0 0 0 1 +Frequency → frequency F Fr Fre Freq BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 0 no 0 10 1 0 0 0 1 +Figure 11: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 1 :().. 5 10 1 0 0 0 1 +SDXL either sdxl S SD SDX SDXL BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 7 1 .. 2 9 1 0 0 0 1 +F On f F F F F BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 7 2 - 1 10 1 0 0 0 1 +Figure 12: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 2 :.- 3 9 1 0 0 0 1 +alignment, as alignment, a al ali alig BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 2 ,-, 3 10 1 0 0 0 1 +human evaluators. human h hu hum huma BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 2 .[],-.-., 9 10 1 0 0 0 1 +human evaluators human h hu hum huma BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 2 -. 2 8 1 0 0 0 1 +Throughout the throughout T Th Thr Thro BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 7 4 -- 2 9 1 0 0 0 1 +FID-[12] and fid-[12] F FI FID FID- BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 -[]-[,]-,-- 11 9 1 0 0 0 1 +of natural of o of of of BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 [].,-- 6 8 1 0 0 0 1 +models [40, models m mo mod mode BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 [,,,],, 7 10 1 0 0 0 1 +tasks such tasks t ta tas task BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 ,- 2 9 1 0 0 0 1 +especially a especially e es esp espe BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 , 1 9 1 0 0 0 1 +become more become b be bec beco BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 ..[]- 5 8 1 0 0 0 1 +is negatively is i is is is BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 , 1 9 1 0 0 0 1 +such models such s su suc such BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 . 1 9 1 0 0 0 1 +FID-vs-CLIP curves fid-vs-clip F FI FID FID- BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 7 4 --.-[]. 7 8 1 0 0 0 1 +improved performance improved i im imp impr BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 (.) 3 9 1 0 0 0 1 +qualitatively (see qualitatively q qu qua qual BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 (..), 5 9 1 0 0 0 1 +versions. Contrarily, versions. v ve ver vers BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 ., 2 9 1 0 0 0 1 +slightly improved slightly s sl sli slig BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 -(-)., 6 8 1 0 0 0 1 +findings of findings f fi fin find BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 .[] 3 9 1 0 0 0 1 +scores, specifically scores, s sc sco scor BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 7 4 ,--. 4 9 1 0 0 0 1 +10k generated 10k 1 10 10k 10k BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 0 0 0 0 7 4 . 1 2 1 0 0 0 1 +14 14 14 1 14 14 14 BLOCKSTART PAGEEND SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 11 no 0 10 0 1 0 0 1 +G Additional g G G G G BLOCKSTART PAGESTART NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 8 0 -- 2 10 1 1 0 0 1 +Figure 13: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 1 :(-)()(). 9 9 1 0 0 0 1 +Prompt: (top) prompt: P Pr Pro Prom BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 1 :()",,,, 8 10 1 0 0 0 1 +sharp focus, sharp s sh sha shar BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 1 1 0 0 0 0 0 8 1 ,"()", 6 10 1 0 0 0 1 +shot, 8k". shot, s sh sho shot BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 8 1 ,".-. 5 2 1 0 0 0 1 +15 15 15 1 15 15 15 BLOCKSTART PAGEEND SAMEFONT HIGHERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 11 no 0 10 0 0 0 0 1 +H Comparison h H H H H BLOCKSTART PAGESTART NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 8 0 .... 4 10 1 1 0 0 1 +'Vibrant portrait 'vibrant ' 'V 'Vi 'Vib BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 8 0 ' 1 10 1 1 0 0 1 +with a with w wi wit with BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 8 0 .' 2 6 1 1 0 0 1 +'A capybara 'a ' 'A 'A 'A BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 1 ' 1 10 1 1 0 0 1 +sitting in sitting s si sit sitt BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 8 1 .' 2 7 1 1 0 0 1 +SD 1-5 sd S SD SD SD BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 2 - 1 10 1 1 0 0 1 +SD 2-1 sd S SD SD SD BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 3 - 1 10 1 0 0 0 1 +SDXL SDXL sdxl S SD SDX SDXL BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 3 no 0 10 1 0 0 0 1 +'Cute adorable 'cute ' 'C 'Cu 'Cut BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 8 3 ',, 3 8 1 0 0 0 1 +cozy interior cozy c co coz cozy BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 8 3 ,,' 3 9 1 0 0 0 1 +digital painting, digital d di dig digi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 8 3 ,,.' 4 10 1 0 0 0 1 +'A portrait 'a ' 'A 'A 'A BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 5 ' 1 8 1 0 0 0 1 +and blue and a an and and BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 8 5 no 0 10 1 0 0 0 1 +Opera House opera O Op Ope Oper BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 5 ""!.' 5 9 1 0 0 0 1 +SD 1-5 sd S SD SD SD BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 7 - 1 10 1 0 0 0 1 +SD 2-1 sd S SD SD SD BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 8 - 1 10 1 0 0 0 1 +SDXL SDXL sdxl S SD SDX SDXL BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 8 no 0 10 1 1 0 0 1 +Figure 14: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 8 : 1 10 1 1 0 0 1 +Diffusion. For diffusion. D Di Dif Diff BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 8 ., 2 9 1 1 0 0 1 +sampler [46] sampler s sa sam samp BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 8 8 []-.[] 6 3 1 1 0 0 1 +16 16 16 1 16 16 16 BLOCKSTART PAGEEND SAMEFONT HIGHERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 11 no 0 10 0 0 0 0 1 +'Monster Baba 'monster ' 'M 'Mo 'Mon BLOCKSTART PAGESTART NEWFONT LOWERFONT 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 8 0 ', 2 10 1 1 0 0 1 +dark horror dark d da dar dark BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 8 0 ,.' 3 8 1 1 0 0 1 +'A young 'a ' 'A 'A 'A BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 0 ' 1 8 1 1 0 0 1 +yellow rose, yellow y ye yel yell BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 8 0 ,.' 3 10 1 1 0 0 1 +SD 1-5 sd S SD SD SD BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 1 - 1 10 1 1 0 0 1 +SD 2-1 sd S SD SD SD BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 1 - 1 10 1 0 0 0 1 +SDXL SDXL sdxl S SD SDX SDXL BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 8 1 no 0 10 1 0 0 0 1 +Figure 15: figure F Fi Fig Figu BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 1 : 1 10 1 0 0 0 1 +Diffusion. For diffusion. D Di Dif Diff BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 1 ., 2 9 1 0 0 0 1 +sampler [46] sampler s sa sam samp BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 8 1 []-.[]. 7 3 1 0 0 0 1 +I Multi-Aspect i I I I I BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 8 3 - 1 10 1 0 0 0 1 +We use we W We We We BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 3 -... 4 10 1 0 0 0 1 +Height Width height H He Hei Heig BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 8 4 no 0 10 0 0 0 0 1 +512 512 512 5 51 512 512 BLOCKSTART PAGEIN NEWFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 4 no 0 8 0 0 0 0 1 +2048 2048 2048 2 20 204 2048 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 8 4 no 0 10 0 0 0 0 1 +0.25 0.25 0.25 0 0. 0.2 0.25 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 8 4 . 1 10 0 0 0 0 1 +512 512 512 5 51 512 512 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 4 no 0 8 0 0 0 0 1 +1984 1984 1984 1 19 198 1984 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 8 4 no 0 10 0 0 0 0 1 +0.26 0.26 0.26 0 0. 0.2 0.26 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 8 4 . 1 10 0 0 0 0 1 +512 512 512 5 51 512 512 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 4 no 0 8 0 0 0 0 1 +1920 1920 1920 1 19 192 1920 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 8 4 no 0 10 0 0 0 0 1 +0.27 0.27 0.27 0 0. 0.2 0.27 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 8 4 . 1 10 0 0 0 0 1 +512 512 512 5 51 512 512 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 4 no 0 8 0 0 0 0 1 +1856 1856 1856 1 18 185 1856 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 8 4 no 0 10 0 0 0 0 1 +0.28 0.28 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1984 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 8 8 no 0 10 0 0 0 0 1 +512 512 512 5 51 512 512 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 8 no 0 8 0 0 0 0 1 +3.88 3.88 3.88 3 3. 3.8 3.88 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 8 8 . 1 10 0 0 0 0 1 +2048 2048 2048 2 20 204 2048 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 1 0 0 0 8 8 no 0 10 0 0 0 0 1 +512 512 512 5 51 512 512 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 8 no 0 8 0 0 0 0 1 +4.0 4.0 4.0 4 4. 4.0 4.0 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 8 8 . 1 8 0 0 0 0 1 +17 17 17 1 17 17 17 BLOCKSTART PAGEEND NEWFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 8 11 no 0 10 0 0 0 0 1 +J Pseudo-code j J J J J BLOCKSTART PAGESTART NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 8 0 - 1 10 0 1 0 0 1 +1 from 1 1 1 1 1 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 8 0 no 0 10 0 1 0 0 1 +2 import 2 2 2 2 2 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 8 0 no 0 4 0 1 0 0 1 +3 3 3 3 3 3 3 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 8 0 no 0 10 0 1 0 0 1 +4 batch_size 4 4 4 4 4 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 8 0 no 0 2 0 1 0 0 1 +5 # 5 5 5 5 5 BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 8 0 #() 3 10 0 1 0 0 1 +6 pooled_dim 6 6 6 6 6 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 8 0 no 0 3 0 1 0 0 1 +7 7 7 7 7 7 7 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 9 0 no 0 10 0 1 0 0 1 +8 def 8 8 8 8 8 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 9 0 (,,): 5 10 0 1 0 0 1 +9 9 9 9 9 9 9 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 1 0 0 0 0 0 0 0 9 1 no 0 10 0 1 0 0 1 +""" """ """ " "" """ """ BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 9 1 """ 3 10 0 1 0 0 1 +10 10 10 1 10 10 10 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 1 no 0 10 0 1 0 0 1 +Classical sinusoidal classical C Cl Cla Clas BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 9 1 no 0 10 0 1 0 0 1 +11 11 11 1 11 11 11 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 1 no 0 10 0 1 0 0 1 +as commonly as a as as as BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 9 1 no 0 10 0 1 0 0 1 +12 12 12 1 12 12 12 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 1 no 0 10 0 0 0 0 1 +: param : : : : : BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 9 1 ::[,] 5 10 0 0 0 0 1 +13 13 13 1 13 13 13 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 1 no 0 10 0 0 0 0 1 +: param : : : : : BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 9 1 :: 2 10 0 0 0 0 1 +14 14 14 1 14 14 14 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 1 no 0 10 0 0 0 0 1 +: param : : : : : BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 9 1 :: 2 10 0 0 0 0 1 +15 15 15 1 15 15 15 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 2 no 0 10 0 0 0 0 1 +: return : : : : : BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 1 0 0 0 0 0 0 0 9 2 ::[,] 5 10 0 0 0 0 1 +16 16 16 1 16 16 16 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 2 no 0 10 0 0 0 0 1 +""" """ """ " "" """ """ BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 9 2 """ 3 10 0 0 0 0 1 +17 17 17 1 17 17 17 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 2 no 0 10 0 0 0 0 1 +... ... ... . .. ... ... BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 ALLCAP NODIGIT 0 0 0 0 0 0 0 0 9 2 ... 3 10 0 0 0 0 1 +18 18 18 1 18 18 18 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 2 no 0 10 0 0 0 0 1 +19 def 19 1 19 19 19 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 2 ( 1 10 0 0 0 0 1 +20 20 20 2 20 20 20 BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 2 no 0 10 0 0 0 0 1 +x : x x x x x BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 9 2 :.,)-.: 7 10 0 0 0 0 1 +21 21 21 2 21 21 21 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 3 no 0 10 0 0 0 0 1 +if x if i if if if BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 9 3 .: 2 10 0 0 0 0 1 +22 22 22 2 22 22 22 BLOCKSTART PAGEIN NEWFONT LOWERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 9 3 no 0 10 0 0 0 0 1 +x = x x x x x BLOCKSTART PAGEIN NEWFONT HIGHERFONT 0 0 NOCAPS NODIGIT 1 0 0 0 0 0 0 0 9 3 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10 0 0 0 0 1 +Aila, Samuli aila, A Ai Ail Aila BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 9 0 ,,,,-.-:-- 10 9 0 0 0 0 1 +Models with models M Mo Mod Mode BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 9 0 .:.,. 5 6 0 0 0 0 1 +[2] David [2] [ [2 [2] [2] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 9 0 [],,,,,,, 9 9 0 0 0 0 1 +Walter Talbot, walter W Wa Wal Walt BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 9 0 ,.:-. 5 10 0 0 0 0 1 +arXiv:2303.04248, 2023. arxiv:2303.04248, a ar arX arXi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 1 0 0 0 9 0 :.,. 4 2 0 0 0 0 1 +[3] Andreas [3] [ [3 [3] [3] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 9 1 [],,,,,, 8 10 0 0 0 0 1 +Karsten Kreis. karsten K Ka Kar Kars BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 9 1 .:-. 4 10 0 0 0 0 1 +arXiv:2304.08818, 2023. arxiv:2304.08818, a ar arX arXi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 1 0 0 0 9 1 :.,. 4 2 0 0 0 0 1 +[4] Jia [4] [ [4 [4] [4] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 9 2 [],,,-,,-.:- 12 10 0 0 0 0 1 +image database. image i im ima imag BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 9 2 .,-. 4 8 0 0 0 0 1 +Ieee, 2009. ieee, I Ie Iee Ieee BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 9 2 ,. 2 1 0 0 0 0 1 +[5] Prafulla [5] [ [5 [5] [5] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 9 2 []..:., 7 10 0 1 0 0 1 +2021. 2021. 2021. 2 20 202 2021 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 1 0 0 0 9 2 . 1 0 0 1 0 0 1 +[6] Tim [6] [ [6 [6] [6] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 9 3 [],,,. 6 10 0 1 0 0 1 +Diffusion Models. diffusion D Di Dif Diff BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 9 3 .,. 3 8 0 1 0 0 1 +[7] Patrick [7] [ [7 [7] [7] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 3 [],,,,. 7 10 0 1 0 0 1 +Structure and structure S St Str Stru BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 10 3 -,. 3 7 0 1 0 0 1 +[8] Weixi [8] [ [8 [8] [8] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 4 [],,-,,,,, 10 10 0 1 0 0 1 +Xin Eric xin X Xi Xin Xin BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 10 4 ,.- 3 10 0 1 0 0 1 +text-to-image synthesis. text-to-image t te tex text BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 10 4 --.:.,. 7 4 0 1 0 0 1 +[9] Seth [9] [ [9 [9] [9] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 4 [].--,. 7 10 0 1 0 0 1 +https://riffusion.com/about. https://riffusion.com/about. https://riffusion.com/about. h ht htt http BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 1 10 4 ://./. 6 2 0 1 0 0 1 +[10] Rinon [10] [ [1 [10 [10] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 5 [],,,,,, 8 9 0 1 0 0 1 +Cohen-Or. An cohen-or. C Co Coh Cohe BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 10 5 -.:--. 6 10 0 1 0 0 1 +arXiv:2208.01618, 2022. arxiv:2208.01618, a ar arX arXi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 1 0 0 0 10 5 :.,. 4 2 0 1 0 0 1 +[11] Nicholas [11] [ [1 [11 [11] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 5 [].,.://.. 10 10 0 1 0 0 1 +org/blog/diffusion-with-offset-noise. org/blog/diffusion-with-offset-noise. org/blog/diffusion-with-offset-noise. o or org org/ BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 0 0 0 0 0 0 10 5 //---. 6 3 0 1 0 0 1 +[12] Martin [12] [ [1 [12 [12] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 6 [],,,,. 7 10 0 0 0 0 1 +Trained by trained T Tr Tra Trai BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 10 6 -.:., 5 9 0 0 0 0 1 +2017. 2017. 2017. 2 20 201 2017 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 1 0 0 0 10 6 . 1 0 0 0 0 0 1 +[13] Jonathan [13] [ [1 [13 [13] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 6 [].-.:.,. 9 10 0 0 0 0 1 +[14] Jonathan [14] [ [1 [14 [14] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 7 [],,.. 6 10 0 0 0 0 1 +arXiv:2006.11239, 2020. arxiv:2006.11239, a ar arX arXi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 1 0 0 0 10 7 :.,. 4 2 0 0 0 0 1 +[15] Jonathan [15] [ [1 [15 [15] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 7 [],,,,,, 8 10 0 0 0 0 1 +Kingma, Ben kingma, K Ki Kin King BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 10 7 ,,,,.: 6 10 0 0 0 0 1 +Video Generation video V Vi Vid Vide BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 10 7 .:.,. 5 6 0 0 0 0 1 +[16] Emiel [16] [ [1 [16 [16] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 8 [],,.:-- 8 10 0 0 0 0 1 +resolution images. resolution r re res reso BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 10 8 .:.,. 5 5 0 0 0 0 1 +[17] Rongjie [17] [ [1 [17 [17] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 8 [],,,,,,,, 10 10 0 1 0 0 1 +Xiang Yin, xiang X Xi Xia Xian BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 10 8 ,.--:--- 8 9 0 1 0 0 1 +Models. arXiv:2301.12661, models. 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On salimans. S Sa Sal Sali BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 10 3 .,. 3 5 0 1 0 0 1 +[30] Alex [30] [ [3 [30 [30] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 3 [],,,,,, 8 10 0 1 0 0 1 +Sutskever, and sutskever, S Su Sut Suts BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 10 3 ,.:- 4 9 0 1 0 0 1 +Guided Diffusion guided G Gu Gui Guid BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 10 3 .:.,. 5 4 0 1 0 0 1 +[31] NovelAI. [31] [ [3 [31 [31] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 4 [].,.://../ 11 10 0 1 0 0 1 +novelai-improvements-on-stable-diffusion-e10d38db82ac. novelai-improvements-on-stable-diffusion-e10d38db82ac. novelai-improvements-on-stable-diffusion-e10d38db82ac. n no nov nove BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 0 0 0 0 10 4 -----. 6 5 0 1 0 0 1 +[32] Adam [32] [ [3 [32 [32] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 4 [],,,,,, 8 9 0 1 0 0 1 +Killeen, Zeming killeen, K Ki Kil Kill BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 11 4 ,,,,,,, 7 9 0 1 0 0 1 +Zach DeVito, zach Z Za Zac Zach BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 11 4 ,,,,,,, 7 10 0 1 0 0 1 +and Soumith and a an and and BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 11 4 .:,-,. 6 9 0 1 0 0 1 +[33] William [33] [ [3 [33 [33] 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0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 11 9 .:.,. 5 5 0 0 0 0 1 +[43] Sitian [43] [ [4 [43 [43] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 10 [],,,,.: 8 10 0 0 0 0 1 +for Language for f fo for for BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 11 10 .:.,. 5 5 0 0 0 0 1 +[44] Uriel [44] [ [4 [44 [44] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 10 [],,,,,,,, 10 10 0 0 0 0 1 +Oron Ashual, oron O Or Oro Oron BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 11 10 ,,,,.--:-- 10 9 0 0 0 0 1 +Generation without generation G Ge Gen Gene BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 11 10 -.:.,. 6 5 0 0 0 0 1 +[45] Jascha [45] [ [4 [45 [45] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 11 []-,,,. 7 10 0 0 0 0 1 +Learning using learning L Le Lea Lear BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 11 11 .:.,. 5 6 0 0 0 0 1 +20 20 20 2 20 20 20 BLOCKSTART PAGEEND SAMEFONT HIGHERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 11 11 no 0 10 0 0 0 0 1 +[46] Jiaming [46] [ [4 [46 [46] BLOCKSTART PAGESTART SAMEFONT LOWERFONT 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 0 [],,..:., 9 10 0 1 0 0 1 +2020. 2020. 2020. 2 20 202 2020 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 1 0 0 0 11 0 . 1 0 0 1 0 0 1 +[47] Yang [47] [ [4 [47 [47] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 0 [],-,,,,. 9 10 0 0 0 0 1 +Score-Based Generative score-based S Sc Sco Scor BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 11 0 -.:.,. 6 9 0 0 0 0 1 +[48] Andreas [48] [ [4 [48 [48] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 1 []..:., 7 10 0 0 0 0 1 +2022. 2022. 2022. 2 20 202 2022 BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 1 0 0 0 11 1 . 1 0 0 0 0 0 1 +[49] Yu [49] [ [4 [49 [49] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 2 [].- 4 10 0 0 0 0 1 +From Human from F Fr Fro From BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 11 2 ./ 2 9 0 0 0 0 1 +Recognition, pages recognition, R Re Rec Reco BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 11 2 ,-,. 4 3 0 0 0 0 1 +[50] Hugo [50] [ [5 [50 [50] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 3 [],,,,-,, 9 10 0 0 0 0 1 +Baptiste Rozière, baptiste B Ba Bap Bapt BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 11 3 ,,,,,, 6 8 0 0 0 0 1 +Edouard Grave, edouard E Ed Edo Edou BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 11 3 ,.:. 4 8 0 0 0 0 1 +arXiv:2302.13971, 2023. arxiv:2302.13971, a ar arX arXi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 1 0 0 0 11 3 :.,. 4 2 0 0 0 0 1 +[51] Jialiang [51] [ [5 [51 [51] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 5 [],-,,,,. 9 10 0 0 0 0 1 +Boosting gui boosting B Bo Boo Boos BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 1 0 0 0 0 0 11 5 .:.,. 5 8 0 0 0 0 1 +[52] Linting [52] [ [5 [52 [52] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 6 [],,,-,,,, 10 10 0 0 0 0 1 +and Colin and a an and and BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 11 6 .:----,. 8 9 0 0 0 0 1 +[53] Jiahui [53] [ [5 [53 [53] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 8 [],,,,,,, 9 9 0 0 0 0 1 +Alexander Ku, alexander A Al Ale Alex BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 1 0 0 0 0 0 0 11 8 ,,,,,,, 7 9 0 0 0 0 1 +Zhang, Jason zhang, Z Zh Zha Zhan BLOCKIN PAGEIN SAMEFONT SAMEFONTSIZE 0 0 INITCAP NODIGIT 0 0 0 0 0 0 0 0 11 8 ,,.--- 6 10 0 0 0 0 1 +generation, 2022. generation, g ge gen gene BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 11 8 ,. 2 1 0 0 0 0 1 +[54] Lvmin [54] [ [5 [54 [54] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 10 [].--. 6 10 0 0 0 0 1 +arXiv:2302.05543, 2023. arxiv:2302.05543, a ar arX arXi BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS CONTAINSDIGITS 0 0 0 0 1 0 0 0 11 10 :.,. 4 2 0 0 0 0 1 +[55] Richard [55] [ [5 [55 [55] BLOCKSTART PAGEIN SAMEFONT SAMEFONTSIZE 0 0 ALLCAP CONTAINSDIGITS 0 0 0 0 0 0 0 0 11 10 [],,.,,. 8 10 0 0 0 0 1 +effectiveness of effectiveness e ef eff effe BLOCKEND PAGEIN SAMEFONT SAMEFONTSIZE 0 0 NOCAPS NODIGIT 0 0 1 0 0 0 0 0 11 10 ,. 2 6 0 0 0 0 1 +21 21 21 2 21 21 21 BLOCKSTART PAGEIN SAMEFONT HIGHERFONT 0 0 NOCAPS ALLDIGIT 0 0 0 0 0 0 0 0 11 11 no 0 10 0 0 0 0 1 + diff --git a/grobid-trainer/resources/dataset/segmentation/corpus/tei/2307.01952v1.training.segmentation.tei.xml b/grobid-trainer/resources/dataset/segmentation/corpus/tei/2307.01952v1.training.segmentation.tei.xml new file mode 100644 index 0000000000..25cbd42971 --- /dev/null +++ b/grobid-trainer/resources/dataset/segmentation/corpus/tei/2307.01952v1.training.segmentation.tei.xml @@ -0,0 +1,101 @@ + + + + + + + SDXL: Improving Latent Diffusion Models for High-Resolution Image Synthesis Dustin Podell Zion English Kyle Lacey Andreas Blattmann Tim Dockhorn Jonas Müller Joe Penna Robin Rombach Stability AI, Applied Research Code: https://github.com/Stability-AI/generative-models Model weights: https://huggingface.co/stabilityai/ Abstract We present SDXL, a latent diffusion model for text-to-image synthesis. Compared to previous versions of Stable Diffusion, SDXL leverages a three times larger UNet backbone: The increase of model parameters is mainly due to more attention blocks and a larger cross-attention context as SDXL uses a second text encoder. We design multiple novel conditioning schemes and train SDXL on multiple aspect ratios. We also introduce a refinement model which is used to improve the visual fidelity of samples generated by SDXL using a post-hoc image-to-image technique. We demonstrate that SDXL shows drastically improved performance compared to previous versions of Stable Diffusion and achieves results competitive with those of black-box state-of-the-art image generators. In the spirit of promoting open research and fostering transparency in large model training and evaluation, we provide access to code and model weights. arXiv:2307.01952v1 [cs.CV] 4 Jul 2023 + + 1 Introduction The last year has brought enormous leaps in deep generative modeling across various data domains, such as natural language [50], audio [17], and visual media [38, 37, 40, 44, 15, 3, 7]. In this report, we focus on the latter and unveil SDXL, a drastically improved version of Stable Diffusion. Stable Diffusion is a latent text-to-image diffusion model (DM) which serves as the foundation for an array of recent advancements in, e.g., 3D classification [43], controllable image editing [54], image personalization [10], synthetic data augmentation [48], graphical user interface prototyping [51], etc. Remarkably, the scope of applications has been extraordinarily extensive, encompassing fields as diverse as music generation [9] and reconstructing images from fMRI brain scans [49]. User studies demonstrate that SDXL consistently surpasses all previous versions of Stable Diffusion by a significant margin (see Fig. 1). In this report, we present the design choices which lead to this boost in performance encompassing i) a 3× larger UNet-backbone compared to previous Stable Diffusion models (Sec. 2.1), ii) two simple yet effective additional conditioning techniques (Sec. 2.2) which do not require any form of additional supervision, and iii) a separate diffusion-based refinement model which applies a noising-denoising process [28] to the latents produced by SDXL to improve the visual quality of its samples (Sec. 2.5). A major concern in the field of visual media creation is that while black-box-models are often recognized as state-of-the-art, the opacity of their architecture prevents faithfully assessing and validating their performance. This lack of transparency hampers reproducibility, stifles innovation, and prevents the community from building upon these models to further the progress of science and art. Moreover, these closed-source strategies make it challenging to assess the biases and limitations of these models in an impartial and objective way, which is crucial for their responsible and ethical deployment. With SDXL we are releasing an open model that achieves competitive performance with black-box image generation models (see Fig. 10 & Fig. 11). 2 Improving Stable Diffusion In this section we present our improvements for the Stable Diffusion architecture. These are modular, and can be used individually or together to extend any model. Although the following strategies are implemented as extensions to latent diffusion models (LDMs) [38], most of them are also applicable to their pixel-space counterparts. Figure 1: Left: Comparing user preferences between SDXL and Stable Diffusion 1.5 & 2.1. While SDXL already clearly outperforms Stable Diffusion 1.5 & 2.1, adding the additional refinement stage boosts performance. Right: Visualization of the two-stage pipeline: We generate initial latents of size 128 × 128 using SDXL. Afterwards, we utilize a specialized high-resolution refinement model and apply SDEdit [28] on the latents generated in the first step, using the same prompt. SDXL and the refinement model use the same autoencoder. 2.1 Architecture & Scale Starting with the seminal works Ho et al. [14] and Song et al. [47], which demonstrated that DMs are powerful generative models for image synthesis, the convolutional UNet [39] architecture has been the dominant architecture for diffusion-based image synthesis. However, with the development + + 2 + + Table 1: Comparison of SDXL and older Stable Diffusion models. Model SDXL SD 1.4/1.5 SD 2.0/2.1 # of UNet params 2.6B 860M 865M Transformer blocks [0, 2, 10] [1, 1, 1, 1] [1, 1, 1, 1] Channel mult. [1, 2, 4] [1, 2, 4, 4] [1, 2, 4, 4] Text encoder CLIP ViT-L & OpenCLIP ViT-bigG CLIP ViT-L OpenCLIP ViT-H Context dim. 2048 768 1024 Pooled text emb. OpenCLIP ViT-bigG N/A N/A of foundational DMs [40, 37, 38], the underlying architecture has constantly evolved: from adding self-attention and improved upscaling layers [5], over cross-attention for text-to-image synthesis [38], to pure transformer-based architectures [33]. We follow this trend and, following Hoogeboom et al. [16], shift the bulk of the transformer com-putation to lower-level features in the UNet. In particular, and in contrast to the original Stable Diffusion architecture, we use a heterogeneous distribution of transformer blocks within the UNet: For efficiency reasons, we omit the transformer block at the highest feature level, use 2 and 10 blocks at the lower levels, and remove the lowest level (8× downsampling) in the UNet altogether -see Tab. 1 for a comparison between the architectures of Stable Diffusion 1.x & 2.x and SDXL. We opt for a more powerful pre-trained text encoder that we use for text conditioning. Specifically, we use OpenCLIP ViT-bigG [19] in combination with CLIP ViT-L [34], where we concatenate the penultimate text encoder outputs along the channel-axis [1]. Besides using cross-attention layers to condition the model on the text-input, we follow [30] and additionally condition the model on the pooled text embedding from the OpenCLIP model. These changes result in a model size of 2.6B parameters in the UNet, see Tab. 1. The text encoders have a total size of 817M parameters. 2.2 Micro-Conditioning Figure 2: Height-vs-Width distribution of our pre-training dataset. Without the proposed size-conditioning, 39% of the data would be discarded due to edge lengths smaller than 256 pixels as visualized by the dashed black lines. Color intensity in each visu-alized cell is proportional to the number of samples. Conditioning the Model on Image Size A no-torious shortcoming of the LDM paradigm [38] is the fact that training a model requires a minimal image size, due to its two-stage architecture. The two main approaches to tackle this problem are ei-ther to discard all training images below a certain minimal resolution (for example, Stable Diffu-sion 1.4/1.5 discarded all images with any size below 512 pixels), or, alternatively, upscale im-ages that are too small. However, depending on the desired image resolution, the former method can lead to significant portions of the training data being discarded, what will likely lead to a loss in performance and hurt generalization. We visualize such effects in Fig. 2 for the dataset on which SDXL was pretrained. For this particular choice of data, discarding all samples below our pretraining resolution of 256 2 pixels would lead to a significant 39% of discarded data. The second method, on the other hand, usually introduces upscaling artifacts which may leak into the final model outputs, causing, for example, blurry samples. Instead, we propose to condition the UNet model on the original image resolution, which is trivially available during training. In particular, we provide the original (i.e., before any rescaling) height and width of the images as an additional conditioning to the model c size = (h original , w original ). Each component is independently embedded using a Fourier feature encoding, and these encodings are concatenated into a single vector that we feed into the model by adding it to the timestep embedding [5]. At inference time, a user can then set the desired apparent resolution of the image via this size-conditioning. Evidently (see Fig. 3), the model has learned to associate the conditioning c size with + + 3 + + c size = (64, 64) c size = (128, 128), c size = (256, 236), c size = (512, 512), 'A robot painted as graffiti on a brick wall. a sidewalk is in front of the wall, and grass is growing out of cracks in the concrete.' 'Panda mad scientist mixing sparkling chemicals, artstation.' Figure 3: The effects of varying the size-conditioning: We show draw 4 samples with the same random seed from SDXL and vary the size-conditioning as depicted above each column. The image quality clearly increases when conditioning on larger image sizes. Samples from the 512 2 model, see Sec. 2.5. Note: For this visualization, we use the 512 × 512 pixel base model (see Sec. 2.5), since the effect of size conditioning is more clearly visible before 1024 × 1024 finetuning. Best viewed zoomed in. resolution-dependent image features, which can be leveraged to modify the appearance of an output corresponding to a given prompt. Note that for the visualization shown in Fig. 3, we visualize samples generated by the 512 × 512 model (see Sec. 2.5 for details), since the effects of the size conditioning are less clearly visible after the subsequent multi-aspect (ratio) finetuning which we use for our final SDXL model. Table 2: Conditioning on the original spatial size of the training examples improves per-formance on class-conditional ImageNet [4] on 512 2 resolution. model FID-5k ↓ IS-5k ↑ CIN-512-only 43.84 110.64 CIN-nocond 39.76 211.50 CIN-size-cond 36.53 215.34 We quantitatively assess the effects of this simple but ef-fective conditioning technique by training and evaluating three LDMs on class conditional ImageNet [4] at spatial size 512 2 : For the first model (CIN-512-only) we discard all training examples with at least one edge smaller than 512 pixels what results in a train dataset of only 70k im-ages. For CIN-nocond we use all training examples but without size conditioning. This additional conditioning is only used for CIN-size-cond. After training we generate 5k samples with 50 DDIM steps [46] and (classifier-free) guidance scale of 5 [13] for every model and compute IS [42] and FID [12] (against the full val-idation set). For CIN-size-cond we generate samples always conditioned on c size = (512, 512). Tab. 2 summarizes the results and verifies that CIN-size-cond improves upon the baseline models in both metrics. We attribute the degraded performance of CIN-512-only to bad generalization due to overfitting on the small training dataset while the effects of a mode of blurry samples in the sample distribution of CIN-nocond result in a reduced FID score. Note that, although we find these classical quantitative scores not to be suitable for evaluating the performance of foundational (text-to-image) DMs [40, 37, 38] (see App. F), they remain reasonable metrics on ImageNet as the neural backbones of FID and IS have been trained on ImageNet itself. Conditioning the Model on Cropping Parameters The first two rows of Fig. 4 illustrate a typical failure mode of previous SD models: Synthesized objects can be cropped, such as the cut-off head of the cat in the left examples for SD 1-5 and SD 2-1. An intuitive explanation for this behavior is the use of random cropping during training of the model: As collating a batch in DL frameworks such as + + 4 + + 'A propaganda poster depicting a cat dressed as french emperor napoleon holding a piece of cheese.' 'a close-up of a fire spitting dragon, cinematic shot.' SD 1-5 SD 2-1 SDXL Figure 4: Comparison of the output of SDXL with previous versions of Stable Diffusion. For each prompt, we show 3 random samples of the respective model for 50 steps of the DDIM sampler [46] and cfg-scale 8.0 [13]. Additional samples in Fig. 14. PyTorch [32] requires tensors of the same size, a typical processing pipeline is to (i) resize an image such that the shortest size matches the desired target size, followed by (ii) randomly cropping the image along the longer axis. While random cropping is a natural form of data augmentation, it can leak into the generated samples, causing the malicious effects shown above. To fix this problem, we propose another simple yet effective conditioning method: During dataloading, we uniformly sample crop coordinates c top and c left (integers specifying the amount of pixels cropped from the top-left corner along the height and width axes, respectively) and feed them into the model as conditioning parameters via Fourier feature embeddings, similar to the size conditioning described above. The concatenated embedding c crop is then used as an additional conditioning parameter. We emphasize that this technique is not limited to LDMs and could be used for any DM. Note that crop-and size-conditioning can be readily combined. In such a case, we concatenate the feature embedding along the channel dimension, before adding it to the timestep embedding in the UNet. Alg. 1 illustrates how we sample c crop and c size during training if such a combination is applied. Given that in our experience large scale datasets are, on average, object-centric, we set (c top , c left ) = (0, 0) during inference and thereby obtain object-centered samples from the trained model. See Fig. 5 for an illustration: By tuning (c top , c left ), we can successfully simulate the amount of cropping during inference. This is a form of conditioning-augmentation, and has been used in various forms with autoregressive [20] models, and more recently with diffusion models [21]. While other methods like data bucketing [31] successfully tackle the same task, we still benefit from cropping-induced data augmentation, while making sure that it does not leak into the generation process -we actually use it to our advantage to gain more control over the image synthesis process. Furthermore, it is easy to implement and can be applied in an online fashion during training, without additional data preprocessing. 2.3 Multi-Aspect Training Real-world datasets include images of widely varying sizes and aspect-ratios (c.f. fig. 2) While the common output resolutions for text-to-image models are square images of 512 × 512 or 1024 × 1024 pixels, we argue that this is a rather unnatural choice, given the widespread distribution and use of landscape (e.g., 16:9) or portrait format screens. Motivated by this, we finetune our model to handle multiple aspect-ratios simultaneously: We follow common practice [31] and partition the data into buckets of different aspect ratios, where we keep the pixel count as close to 1024 2 pixels as possibly, varying height and width accordingly in multiples + + 5 + + Algorithm 1 Conditioning pipeline for size-and crop-conditioning Require: Training dataset of images D, target image size for training s = (h tgt , w tgt ) Require: Resizing function R, cropping function function C Require: Model train step T converged ← False while not converged do x ∼ D w original ← width(x) h original ← height(x) c size ← (h original , w original ) x ← R(x, s) ▷ resize smaller image size to target size s if h original ≤ w original then c left ∼ U (0, width(x) -s w ) ▷ sample c left from discrete uniform distribution c top = 0 else if h original > w original then c top ∼ U (0, height(x) -s h ) ▷ sample c top from discrete uniform distribution c left = 0 end if c crop ← (c top , c left ) x ← C(x, s, c crop ) ▷ crop image to size s with top-left coordinate (c top , c left ) converged ← T (x, c size , c crop ) ▷ train model conditioned on c size and c crop end while c crop = (0, 0) c crop = (0, 256), c crop = (256, 0), c crop = (512, 512), 'An astronaut riding a pig, highly realistic dslr photo, cinematic shot.' 'A capybara made of lego sitting in a realistic, natural field.' Figure 5: Varying the crop conditioning as discussed in Sec. 2.2. See Fig. 4 and Fig. 14 for samples from SD 1.5 and SD 2.1 which provide no explicit control of this parameter and thus introduce cropping artifacts. Samples from the 512 2 model, see Sec. 2.5. + + 6 + + of 64. A full list of all aspect ratios used for training is provided in App. I. During optimization, a training batch is composed of images from the same bucket, and we alternate between bucket sizes for each training step. Additionally, the model receives the bucket size (or, target size) as a conditioning, represented as a tuple of integers c ar = (h tgt , w tgt ) which are embedded into a Fourier space in analogy to the size-and crop-conditionings described above. In practice, we apply multi-aspect training as a finetuning stage after pretraining the model at a fixed aspect-ratio and resolution and combine it with the conditioning techniques introduced in Sec. 2.2 via concatenation along the channel axis. Fig. 16 in App. J provides python-code for this operation. Note that crop-conditioning and multi-aspect training are complementary operations, and crop-conditioning then only works within the bucket boundaries (usually 64 pixels). For ease of implementation, however, we opt to keep this control parameter for multi-aspect models. 2.4 Improved Autoencoder Table 3: Autoencoder reconstruction performance on the COCO2017 [26] validation split, images of size 256 × 256 pixels. Note: Stable Diffusion 2.x uses an improved version of Stable Diffusion 1.x's autoencoder, where the decoder was finetuned with a reduced weight on the perceptual loss [55], and used more compute. Note that our new autoencoder is trained from scratch. model PNSR ↑ SSIM ↑ LPIPS ↓ rFID ↓ SDXL-VAE 24.7 0.73 0.88 4.4 SD-VAE 1.x 23.4 0.69 0.96 5.0 SD-VAE 2.x 24.5 0.71 0.92 4.7 Stable Diffusion is a LDM, operating in a pre-trained, learned (and fixed) latent space of an autoencoder. While the bulk of the semantic composition is done by the LDM [38], we can improve local, high-frequency details in gener-ated images by improving the autoencoder. To this end, we train the same autoencoder archi-tecture used for the original Stable Diffusion at a larger batch-size (256 vs 9) and additionally track the weights with an exponential moving average. The resulting autoencoder outperforms the original model in all evaluated reconstruction metrics, see Tab. 3. We use this autoencoder for all of our experiments. 2.5 Putting Everything Together We train the final model, SDXL, in a multi-stage procedure. SDXL uses the autoencoder from Sec. 2.4 and a discrete-time diffusion schedule [14, 45] with 1000 steps. First, we pretrain a base model (see Tab. 1) on an internal dataset whose height-and width-distribution is visualized in Fig. 2 for 600 000 optimization steps at a resolution of 256 × 256 pixels and a batch-size of 2048, using size-and crop-conditioning as described in Sec. 2.2. We continue training on 512 × 512 pixel images for another 200 000 optimization steps, and finally utilize multi-aspect training (Sec. 2.3) in combination with an offset-noise [11, 25] level of 0.05 to train the model on different aspect ratios (Sec. 2.3, App. I) of ∼ 1024 × 1024 pixel area. Refinement Stage Empirically, we find that the resulting model sometimes yields samples of low local quality, see Fig. 6. To improve sample quality, we train a separate LDM in the same latent space, which is specialized on high-quality, high resolution data and employ a noising-denoising process as introduced by SDEdit [28] on the samples from the base model. We follow [1] and specialize this refinement model on the first 200 (discrete) noise scales. During inference, we render latents from the base SDXL, and directly diffuse and denoise them in latent space with the refinement model (see Fig. 1), using the same text input. We note that this step is optional, but improves sample quality for detailed backgrounds and human faces, as demonstrated in Fig. 6 and Fig. 13. To assess the performance of our model (with and without refinement stage), we conduct a user study, and let users pick their favorite generation from the following four models: SDXL, SDXL (with refiner), Stable Diffusion 1.5 and Stable Diffusion 2.1. The results demonstrate the SDXL with the refinement stage is the highest rated choice, and outperforms Stable Diffusion 1.5 & 2.1 by a significant margin (win rates: SDXL w/ refinement: 48.44%, SDXL base: 36.93%, Stable Diffusion 1.5: 7.91%, Stable Diffusion 2.1: 6.71%). See Fig. 1, which also provides an overview of the full pipeline. However, when using classical performance metrics such as FID and CLIP scores the improvements of SDXL over previous methods are not reflected as shown in Fig. 12 and discussed in App. F. This aligns with and further backs the findings of Kirstain et al. [23]. + + 7 + + Figure 6: 1024 2 samples (with zoom-ins) from SDXL without (left) and with (right) the refinement model discussed. Prompt: "Epic long distance cityscape photo of New York City flooded by the ocean and overgrown buildings and jungle ruins in rainforest, at sunset, cinematic shot, highly detailed, 8k, golden light". See Fig. 13 for additional samples. 3 Future Work This report presents a preliminary analysis of improvements to the foundation model Stable Diffusion for text-to-image synthesis. While we achieve significant improvements in synthesized image quality, prompt adherence and composition, in the following, we discuss a few aspects for which we believe the model may be improved further: • Single stage: Currently, we generate the best samples from SDXL using a two-stage approach with an additional refinement model. This results in having to load two large models into memory, hampering accessibility and sampling speed. Future work should investigate ways to provide a single stage of equal or better quality. • Text synthesis: While the scale and the larger text encoder (OpenCLIP ViT-bigG [19]) help to improve the text rendering capabilities over previous versions of Stable Diffusion, incorporating byte-level tokenizers [52, 27] or simply scaling the model to larger sizes [53, 40] may further improve text synthesis. • Architecture: During the exploration stage of this work, we briefly experimented with transformer-based architectures such as UViT [16] and DiT [33], but found no immediate benefit. We remain, however, optimistic that a careful hyperparameter study will eventually enable scaling to much larger transformer-dominated architectures. • Distillation: While our improvements over the original Stable Diffusion model are significant, they come at the price of increased inference cost (both in VRAM and sampling speed). Future work will thus focus on decreasing the compute needed for inference, and increased sampling speed, for example through guidance-[29], knowledge-[6, 22, 24] and progressive distillation [41, 2, 29]. • Our model is trained in the discrete-time formulation of [14], and requires offset-noise [11, 25] for aesthetically pleasing results. The EDM-framework of Karras et al. [21] is a promising candidate for future model training, as its formulation in continuous time allows for increased sampling flexibility and does not require noise-schedule corrections. + + 8 + +
Appendix
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A Acknowledgements We thank all the folks at StabilityAI who worked on comparisons, code, etc, in particular: Alex Goodwin, Benjamin Aubin, Bill Cusick, Dennis Nitrosocke Niedworok, Dominik Lorenz, Harry Saini, Ian Johnson, Ju Huo, Katie May, Mohamad Diab, Peter Baylies, Rahim Entezari, Yam Levi, Yannik Marek, Yizhou Zheng. We also thank ChatGPT for providing writing assistance.
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B Limitations 'A close up of a handpalm with leaves growing from it.' 'An empty fireplace with a television above it. The TV shows a lion hugging a giraffe.' 'A grand piano with a white bench.' 'Three quarters view of a rusty old red pickup truck with white doors and a smashed windshield.' Figure 7: Failure cases of SDXL despite large improvements compared to previous versions of Stable Diffusion, the model sometimes still struggles with very complex prompts involving detailed spatial arrangements and detailed descriptions (e.g. top left example). Moreover, hands are not yet always correctly generated (e.g. top left) and the model sometimes suffers from two concepts bleeding into one another (e.g. bottom right example). All examples are random samples generated with 50 steps of the DDIM sampler [46] and cfg-scale 8.0 [13]. While our model has demonstrated impressive capabilities in generating realistic images and synthe-sizing complex scenes, it is important to acknowledge its inherent limitations. Understanding these limitations is crucial for further improvements and ensuring responsible use of the technology. Firstly, the model may encounter challenges when synthesizing intricate structures, such as human hands (see Fig. 7, top left). Although it has been trained on a diverse range of data, the complexity of human anatomy poses a difficulty in achieving accurate representations consistently. This limitation suggests the need for further scaling and training techniques specifically targeting the synthesis of fine-grained details. A reason for this occurring might be that hands and similar objects appear with very high variance in photographs and it is hard for the model to extract the knowledge of the real 3D shape and physical limitations in that case. Secondly, while the model achieves a remarkable level of realism in its generated images, it is important to note that it does not attain perfect photorealism. Certain nuances, such as subtle lighting effects or minute texture variations, may still be absent or less faithfully represented in the generated images. This limitation implies that caution should be exercised when relying solely on model-generated visuals for applications that require a high degree of visual fidelity. Furthermore, the model's training process heavily relies on large-scale datasets, which can inadver-tently introduce social and racial biases. As a result, the model may inadvertently exacerbate these biases when generating images or inferring visual attributes. In certain cases where samples contain multiple objects or subjects, the model may exhibit a phe-nomenon known as "concept bleeding". This issue manifests as the unintended merging or overlap of distinct visual elements. For instance, in Fig. 14, an orange sunglass is observed, which indicates an instance of concept bleeding from the orange sweater. Another case of this can be seen in Fig. 8, the penguin is supposed to have a "blue hat" and "red gloves", but is instead generated with blue
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gloves and a red hat. Recognizing and addressing such occurrences is essential for refining the model's ability to accurately separate and represent individual objects within complex scenes. The root cause of this may lie in the used pretrained text-encoders: firstly, they are trained to compress all information into a single token, so they may fail at binding only the right attributes and objects, Feng et al. [8] mitigate this issue by explicitly encoding word relationships into the encoding. Secondly, the contrastive loss may also contribute to this, since negative examples with a different binding are needed within the same batch [35]. Additionally, while our model represents a significant advancement over previous iterations of SD, it still encounters difficulties when rendering long, legible text. Occasionally, the generated text may contain random characters or exhibit inconsistencies, as illustrated in Fig. 8. Overcoming this limitation requires further investigation and development of techniques that enhance the model's text generation capabilities, particularly for extended textual content -see for example the work of Liu et al. [27], who propose to enhance text rendering capabilities via character-level text tokenizers. Alternatively, scaling the model does further improve text synthesis [53, 40]. In conclusion, our model exhibits notable strengths in image synthesis, but it is not exempt from certain limitations. The challenges associated with synthesizing intricate structures, achieving perfect photorealism, further addressing biases, mitigating concept bleeding, and improving text rendering highlight avenues for future research and optimization.
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C Diffusion Models In this section, we give a concise summary of DMs. We consider the continuous-time DM frame-work [47] and follow the presentation of Karras et al. [21]. Let p data (x 0 ) denote the data distribution and let p(x; σ) be the distribution obtained by adding i.i.d. σ 2 -variance Gaussian noise to the data. For sufficiently large σ max , p(x; σ max 2 ) is almost indistinguishable from σ 2 max -variance Gaussian noise. Capitalizing on this observation, DMs sample high variance Gaussian noise x M ∼ N (0, σ max 2 ) and sequentially denoise x M into x i ∼ p(x i ; σ i ), i ∈ {0, . . . , M }, with σ i < σ i+1 and σ M = σ max . For a well-trained DM and σ 0 = 0 the resulting x 0 is distributed according to the data. Sampling. In practice, this iterative denoising process explained above can be implemented through the numerical simulation of the Probability Flow ordinary differential equation (ODE) [47] dx = -σ(t)σ(t)∇ x log p(x; σ(t)) dt, (1) where ∇ x log p(x; σ) is the score function [18]. The schedule σ(t): [0, 1] → R + is user-specified and σ(t) denotes the time derivative of σ(t). Alternatively, we may also numerically simulate a stochastic differential equation (SDE) [47, 21]: dx = -σ(t)σ(t)∇ x log p(x; σ(t)) dt Probability Flow ODE; see Eq. (1) -β(t)σ 2 (t)∇ x log p(x; σ(t)) dt + 2β(t)σ(t) dω t Langevin diffusion component , (2) where dω t is the standard Wiener process. In principle, simulating either the Probability Flow ODE or the SDE above results in samples from the same distribution. Training. DM training reduces to learning a model s θ (x; σ) for the score function ∇ x log p(x; σ). The model can, for example, be parameterized as ∇ x log p(x; σ) ≈ s θ (x; σ) = (D θ (x; σ) -x)/σ 2 [21], where D θ is a learnable denoiser that, given a noisy data point x 0 + n, x 0 ∼ p data (x 0 ), n ∼ N 0, σ 2 I d , and conditioned on the noise level σ, tries to predict the clean x 0 . The denoiser D θ (or equivalently the score model) can be trained via denoising score matching (DSM) E (x0,c)∼p data (x0,c),(σ,n)∼p(σ,n) λ σ ∥D θ (x 0 + n; σ, c) -x 0 ∥ 2 2 , (3) where p(σ, n) = p(σ) N n; 0, σ 2 , p(σ) is a distribution over noise levels σ, λ σ : R + → R + is a weighting function, and c is an arbitrary conditioning signal, e.g., a class label, a text prompt, or a combination thereof. In this work, we choose p(σ) to be a discrete distributions over 1000 noise levels and set λ σ = σ -2 similar to prior works [14, 38, 45]. Classifier-free guidance. Classifier-free guidance [13] is a technique to guide the iterative sampling process of a DM towards a conditioning signal c by mixing the predictions of a conditional and an unconditional model D w (x; σ, c) = (1 + w)D(x; σ, c) -wD(x; σ), (4) where w ≥ 0 is the guidance strength. In practice, the unconditional model can be trained jointly alongside the conditional model in a single network by randomly replacing the conditional signal c with a null embedding in Eq. (3), e.g., 10% of the time [13]. Classifier-free guidance is widely used to improve the sampling quality, trading for diversity, of text-to-image DMs [30, 38].
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D Comparison to the State of the Art Figure 8: Qualitative comparison of SDXL with DeepFloyd IF, DALLE-2, Bing Image Creator, and Midjourney v5.2. To mitigate any bias arising from cherry-picking, Parti (P2) prompts were randomly selected. Seed 3 was uniformly applied across all models in which such a parameter could be designated. For models without a seed-setting feature, the first generated image is included.
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E Comparison to Midjourney v5.1 E.1 Overall Votes To asses the generation quality of SDXL we perform a user study against the state of the art text-to-image generation platform Midjourney 1 . As the source for image captions we use the PartiPrompts (P2) benchmark [53], that was introduced to compare large text-to-image model on various challeng-ing prompts. For our study, we choose five random prompts from each category, and generate four 1024 × 1024 images by both Midjourney (v5.1, with a set seed of 2) and SDXL for each prompt. These images were then presented to the AWS GroundTruth taskforce, who voted based on adherence to the prompt. The results of these votes are illustrated in Fig. 9. Overall, there is a slight preferance for SDXL over Midjourney in terms of prompt adherence. Vanilla 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Frequency → Figure 9: Results from 17,153 user preference comparisons between SDXL v0.9 and Midjourney v5.1, which was the latest version available at the time. The comparisons span all "categories" and "challenges" in the PartiPrompts (P2) benchmark. Notably, SDXL was favored 54.9% of the time over Midjourney V5.1. Preliminary testing indicates that the recently-released Midjourney V5.2 has lower prompt comprehension than its predecessor, but the laborious process of generating multiple prompts hampers the speed of conducting broader tests. E.2 Category & challenge comparisons on PartiPrompts (P2) Each prompt from the P2 benchmark is organized into a category and a challenge, each focus on different difficult aspects of the generation process. We show the comparisons for each category (Fig. 10) and challenge (Fig. 11) of P2 below. In four out of six categories SDXL outperforms Midjourney, and in seven out of ten challenges there is no significant difference between both models or SDXL outperforms Midjourney. Food & Beverage Animals Artifacts Arts Illustrations Abstract 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Frequency → Figure 10: User preference comparison of SDXL (without refinement model) and Midjourney V5.1 across particular text categories. SDXL outperforms Midjourney V5.1 in all but two categories.
+ + 1 We compare against v5.1 since that was the best version available at that time. + + 13 + +
Imagination Writing & Symbols Quantity Complex Fine-grained Detail Perspective Style & Format Simple Detail Linguistic Structures Properties & Positioning 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Frequency → Figure 11: Preference comparisons of SDXL (with refinement model) to Midjourney V5.1 on complex prompts. SDXL either outperforms or is statistically equal to Midjourney V5.1 in 7 out of 10 categories. F On FID Assessment of Generative Text-Image Foundation Models Figure 12: Plotting FID vs CLIP score for different cfg scales. SDXL shows only slightly improved text-alignment, as measured by CLIP-score, compared to previous versions that do not align with the judgement of human evaluators. Even further and similar as in [23], FID are worse than for both SD-1.5 and SD-2.1, while human evaluators clearly prefer the generations of SD-XL over those of these previous models. Throughout the last years it has been common practice for generative text-to-image models to assess FID-[12] and CLIP-scores [34, 36] in a zero-shot setting on complex, small-scale text-image datasets of natural images such as COCO [26]. However, with the advent of foundational text-to-image models [40, 37, 38, 1], which are not only targeting visual compositionality, but also at other difficult tasks such as deep text understanding, fine-grained distinction between unique artistic styles and especially a pronounced sense of visual aesthetics, this particular form of model evaluation has become more and more questionable. Kirstain et al. [23] demonstrates that COCO zero-shot FID is negatively correlated with visual aesthetics, and such measuring the generative performance of such models should be rather done by human evaluators. We investigate this for SDXL and visualize FID-vs-CLIP curves in Fig. 12 for 10k text-image pairs from COCO [26]. Despite its drastically improved performance as measured quantitatively by asking human assessors (see Fig. 1) as well as qualitatively (see Fig. 4 and Fig. 14), SDXL does not achieve better FID scores than the previous SD versions. Contrarily, FID for SDXL is the worst of all three compared models while only showing slightly improved CLIP-scores (measured with OpenClip ViT g-14). Thus, our results back the findings of Kirstain et al. [23] and further emphasize the need for additional quantitative performance scores, specifically for text-to-image foundation models. All scores have been evaluated based on 10k generated examples.
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G Additional Comparison between Single-and Two-Stage SDXL pipeline Figure 13: SDXL samples (with zoom-ins) without (left) and with (right) the refinement model discussed. Prompt: (top) "close up headshot, futuristic young woman, wild hair sly smile in front of gigantic UFO, dslr, sharp focus, dynamic composition" (bottom) "Three people having dinner at a table at new years eve, cinematic shot, 8k". Zoom-in for details.
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H Comparison between SD 1.5 vs. SD 2.1 vs. SDXL 'Vibrant portrait painting of Salvador Dalí with a robotic half face.' 'A capybara made of voxels sitting in a field.' SD 1-5 SD 2-1 SDXL 'Cute adorable little goat, unreal engine, cozy interior lighting, art station, detailed' digital painting, cinematic, octane rendering.' 'A portrait photo of a kangaroo wearing an orange hoodie and blue sunglasses standing on the grass in front of the Sydney Opera House holding a sign on the chest that says "SDXL"!.' SD 1-5 SD 2-1 SDXL Figure 14: Additional results for the comparison of the output of SDXL with previous versions of Stable Diffusion. For each prompt, we show 3 random samples of the respective model for 50 steps of the DDIM sampler [46] and cfg-scale 8.0 [13]
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'Monster Baba yaga house with in a forest, dark horror style, black and white.' 'A young badger delicately sniffing a yellow rose, richly textured oil painting.' SD 1-5 SD 2-1 SDXL Figure 15: Additional results for the comparison of the output of SDXL with previous versions of Stable Diffusion. For each prompt, we show 3 random samples of the respective model for 50 steps of the DDIM sampler [46] and cfg-scale 8.0 [13]. I Multi-Aspect Training Hyperparameters We use the following image resolutions for mixed-aspect ratio finetuning as described in Sec. 2.3. Height Width Aspect Ratio 512 2048 0.25 512 1984 0.26 512 1920 0.27 512 1856 0.28 576 1792 0.32 576 1728 0.33 576 1664 0.35 640 1600 0.4 640 1536 0.42 704 1472 0.48 704 1408 0.5 704 1344 0.52 768 1344 0.57 768 1280 0.6 832 1216 0.68 832 1152 0.72 896 1152 0.78 896 1088 0.82 960 1088 0.88 960 1024 0.94 Height Width Aspect Ratio 1024 1024 1.0 1024 960 1.07 1088 960 1.13 1088 896 1.21 1152 896 1.29 1152 832 1.38 1216 832 1.46 1280 768 1.67 1344 768 1.75 1408 704 2.0 1472 704 2.09 1536 640 2.4 1600 640 2.5 1664 576 2.89 1728 576 3.0 1792 576 3.11 1856 512 3.62 1920 512 3.75 1984 512 3.88 2048 512 4.0
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J Pseudo-code for Conditioning Concatenation along the Channel Axis 1 from einops import rearrange 2 import torch 3 4 batch_size =16 5 # channel dimension of pooled output of text encoder ( s ) 6 pooled_dim = 512 7 8 def fourier_embe dding ( inputs , outdim =256 , max_period =10000) :
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""" 10 Classical sinusoidal timestep embedding 11 as commonly used in diffusion models 12 : param inputs : batch of integer scalars shape [b ,] 13 : param outdim : embedding dimension 14 : param max_period : max freq added 15 : return : batch of embeddings of shape [b , outdim ] 16 """ 17 ... 18 19 def c a t_ a l o n g _ c h a n n e l_ d im ( 20 x : torch . Tensor ,) -> torch . Tensor : 21 if x . ndim == 1: 22 x = x [... , None ] 23 assert x . ndim == 2 24 b , d_in = x . shape 25 x = rearrange (x , " b din -> ( b din ) " ) 26 # fourier fn adds additional dimension 27 emb = fourie r_embedding ( x ) 28 d_f = emb . shape [ -1] 29 emb = rearrange ( emb , " ( b din ) df -> b ( din df ) " , 30 b =b , din = d_in , df = d_f ) 31 return emb 32 33 def conc at_embed dings ( 34 # batch of size and crop conditioning cf . Sec . 3.2 35 c_size : torch . Tensor , 36 c_crop : torch . Tensor , 37 # batch of aspect ratio conditioning cf . Sec . 3.3 38 c_ar : torch . Tensor , 39 # final output of text encoders after pooling cf . Sec . 3.1 40 c_pooled_txt : torch . Tensor , ) -> torch . Tensor : 41 # fourier feature for size conditioning 42 c_size_emb = c a t_ along _chann el_dim ( c_size ) 43 # fourier feature for size conditioning 44 c_crop_emb = c a t_ along _chann el_dim ( c_crop ) 45 # fourier feature for size conditioning 46 c_ar_emb = c at _ al on g_chan nel_d im ( c_ar ) 47 # the concatenated output is mapped to the same 48 # channel dimension than the noise level conditioning 49 # and added to that conditioning before being fed to the unet 50 return torch . cat ([ c_pooled_txt , 51 c_size_emb , 52 c_crop_emb , 53 c_ar_emb ] , dim =1) 54 55 # simulating c_size and c_crop as in Sec . 3.2 56 c_size = torch . zeros (( batch_size , 2) ) . long () 57 c_crop = torch . zeros (( batch_size , 2) ) . long () 58 # simulating c_ar and pooled text encoder output as in Sec . 3.3 59 c_ar = torch . zeros (( batch_size , 2) ) . long () 60 c_pooled = torch . zeros (( batch_size , pooled_dim ) ) . long () 61 62 # get concatenated embedding 63 c_concat = conc at_embeddings ( c_size , c_crop , c_ar , c_pooled ) Figure 16: Python code for concatenating the additional conditionings introduced in Secs. 2.1 to 2.3 along the channel dimension.
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GLIDE: Towards Photorealistic Image Generation and Editing with Text-Guided Diffusion Models. arXiv:2112.10741, 2021. [31] NovelAI. Novelai improvements on stable diffusion, 2023. URL https://blog.novelai.net/ novelai-improvements-on-stable-diffusion-e10d38db82ac. [32] Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Köpf, Edward Yang, Zach DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. Pytorch: An imperative style, high-performance deep learning library, 2019. [33] William Peebles and Saining Xie. Scalable Diffusion Models with Transformers. arXiv:2212.09748, 2022. [34] Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, Gretchen Krueger, and Ilya Sutskever. Learning Transferable Visual Models From Natural Language Supervision. arXiv:2103.00020, 2021. [35] Aditya Ramesh. How dall•e 2 works, 2022. URL http://adityaramesh.com/posts/dalle2/dalle2. html. [36] Aditya Ramesh, Mikhail Pavlov, Gabriel Goh, Scott Gray, Chelsea Voss, Alec Radford, Mark Chen, and Ilya Sutskever. Zero-shot text-to-image generation, 2021. [37] Aditya Ramesh, Prafulla Dhariwal, Alex Nichol, Casey Chu, and Mark Chen. Hierarchical Text-Conditional Image Generation with CLIP Latents. arXiv:2204.06125, 2022. [38] Robin Rombach, Andreas Blattmann, Dominik Lorenz, Patrick Esser, and Björn Ommer. High-Resolution Image Synthesis with Latent Diffusion Models. arXiv preprint arXiv:2112.10752, 2021. [39] Olaf Ronneberger, Philipp Fischer, and Thomas Brox. U-Net: Convolutional Networks for Biomedical Image Segmentation. arXiv:1505.04597, 2015. 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[50] Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurelien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. LLaMA: Open and Efficient Foundation Language Models. arXiv:2302.13971, 2023. [51] Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais, Binbin Xu, Pierre Louis Bernard, and Gérard Dray. Boosting gui prototyping with diffusion models. arXiv preprint arXiv:2306.06233, 2023. [52] Linting Xue, Aditya Barua, Noah Constant, Rami Al-Rfou, Sharan Narang, Mihir Kale, Adam Roberts, and Colin Raffel. Byt5: Towards a token-free future with pre-trained byte-to-byte models, 2022. [53] Jiahui Yu, Yuanzhong Xu, Jing Yu Koh, Thang Luong, Gunjan Baid, Zirui Wang, Vijay Vasudevan, Alexander Ku, Yinfei Yang, Burcu Karagol Ayan, Ben Hutchinson, Wei Han, Zarana Parekh, Xin Li, Han Zhang, Jason Baldridge, and Yonghui Wu. 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+
diff --git a/grobid-trainer/resources/dataset/segmentation/corpus/tei/3_10.1128_spectrum.00751-24.training.segmentation.tei.xml b/grobid-trainer/resources/dataset/segmentation/corpus/tei/3_10.1128_spectrum.00751-24.training.segmentation.tei.xml index 51d75268a9..0e7a942110 100644 --- a/grobid-trainer/resources/dataset/segmentation/corpus/tei/3_10.1128_spectrum.00751-24.training.segmentation.tei.xml +++ b/grobid-trainer/resources/dataset/segmentation/corpus/tei/3_10.1128_spectrum.00751-24.training.segmentation.tei.xml @@ -13,6 +13,7 @@ October 2024 Volume 12 Issue 10 10.1128/spectrum.00751-24 2 + Downloaded from https://journals.asm.org/journal/spectrum on 10 October 2024 by 2a01:e0a:d12:4600:6f65:dae8:67:55e1. MATERIALS AND METHODS Sample collection, susceptibility testing, and DNA isolation One E. coli isolate named CrieF1144 was selected for this study from the set of 11 samples collected by the Armenia Center of Hygiene and Epidemiology as a part of regular food and water monitoring activities in 2021. CrieF1144 was isolated from municipal water after an accident in the water supply system in a residential build ing. Worth noting, this water is usually used as drinking fresh water in Armenia, as it is supplied from glaciers and mountain rivers. Matrix-assisted laser desorption/ion ization time-of-flight mass spectrometry (MALDI-TOF) with Microflex LT system and the MALDI Biotyper Compass v.4.1.80 software (Bruker Daltonics, Germany) were used for species detection, and an antimicrobial susceptibility test for CrieF1144 E. coli was performed using the minimum inhibitory concentration (MIC) method with a Sensititre Analyzer (TREK Diagnostics Systems, USA). The susceptibility/resistance was checked for amikacin, ampicillin, ampicillin/sulbactam, cefepime, ceftazidime, cefurox ime, ciprofloxacin, levofloxacin, trimethoprim/sulfamethoxazole, colistin, imipenem, and tigecycline. Broth microdilution method was used for colistin resistance determination. SWIN software was applied to interpret the results in accordance with EUCAST version 11.0 (http://www.eucast.org, accessed in 2021). E. сoli ATCC25922 and E. coli ATCC35218 were used for routine internal quality control tests for MIC determination. Real-time PCR assay for mcr-1 Real-time polymerase chain reaction (qPCR) was performed using the PCR-kit «AmpliS ens MDR MCR-1-FL» (Central Research Institute of Epidemiology, Moscow, Russia). The qPCR assay was performed on a Rotor-Gene 6000 (Corbett Research, Mortlake, Australia), and the data were analyzed with the Rotor-Gene 6000 v1.8 software. Whole-genome sequencing Genomic DNA was isolated with the DNeasy Blood and Tissue kit (Qiagen, Hilden, Germany). Quantity was evaluated by fluorimetry with Qubit 4.0 (Thermo Fisher Scientific, USA), then the Nextera DNA Sample Prep Kit (Illumina, San Diego, CA, USA) was used for paired-end library preparation and whole genome sequencing (WGS) of the isolate on Illumina NextSeq 2000 platform (Illumina, San Diego, CA, USA). Oxford Nanopore MinION sequencing system (Oxford Nanopore Technologies, Oxford, UK) with the Rapid Barcoding Sequencing kit SQK-RBK004 (Oxford Nanopore Technologies, Oxford, UK) was used for long-read WGS. The libraries were prepared according to the manufacturer's protocols and were sequenced on FLO-MIN106 R9.4 flow cell with a standard 72-h sequencing protocol using the MinKNOW software version 22.03 (Oxford Nanopore Technologies, Oxford, UK). Genome assembly, data processing, and annotation Base calling of the raw MinION data was performed with Guppy Basecaller version 6.4.6 (Oxford Nanopore Technologies, Oxford, UK), whereas demultiplexing was performed using Guppy barcoding software version 6.4.6 (Oxford Nanopore Technologies, Oxford, UK). Hybrid short-and long-read assembly was generated using Unicycler version 0.5.0 (bold mode, SPAdes version 3.15.4 for short reads) (18). The contigs with a length lower than 1,000 bp were discarded. The genome assembly was uploaded to NCBI Genbank under the project number PRJNA1075679, with the genome accession number JBAGRT000000000. Resfinder 4.3.0 software was used for antimicrobial gene detection (https:// cge.cbs.dtu.dk/services/ResFinder/, accessed on 20 January 2024, using default parameters) and point mutation analysis. Virulence factors were searched in VFDB (http://www.mgc.ac.cn/VFs/main.htm, accessed on 20 January 2024, using default parameters). Plasmid replicon types, predicted mobility, and other plasmid annotation @@ -77,7 +78,7 @@ Thus, the hybrid assembly of the genome studied allowed us not only to reveal the accurate structure of the chromosome and plasmids, but also to gain insights into possible colistin resistance mechanisms for the CrieF1144 isolate. In summary, this study focuses on high-resolution genomic analysis of the E. coli isolate from drinking water, aiming to understand the genetic structure and pathogene sis of this environmental strain. As the prevalence and dissemination of MDR E. coli is a significant concern in the context of both human and animal populations, a compre hensive One Health-based approach is necessary to study this important pathogen. This approach involves the interconnections between human, animal, and environmen tal health, and establishes the collaboration between various scientific and medical fields to mitigate the growing threat of AMR spread and associated risks in urban environments (37). In the current study, we performed WGS-based characterization and phenotypic AMR analysis of the E. coli isolate obtained from drinking water, and revealed the possible mechanism of colistin resistance transfer. The results emphasize the importance of WGS-based monitoring of mcr-harboring Enterobacteriaceae in both clinical and environmental settings in agreement with the One Health concept. -
ACKNOWLEDGMENTS This research was funded by a grant from the Ministry of Science and Higher Education of the Russian Federation (agreement No. 075-15-2019-1666). All authors contributed to this study. A.K.: investigation, methodology, validation, visualization, writing -original draft; A.S.: conceptualization, data curation, formal analysis, validation, visualization, writing -original draft; I.M.: resources, project administration; N.K.: investigation, methodology; A.G.: project administration, funding acquisition; Y.M.: conceptualization, supervision, validation, writing -review and editing; V.A.: resources, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript.
+
ACKNOWLEDGMENTS This research was funded by a grant from the Ministry of Science and Higher Education of the Russian Federation (agreement No. 075-15-2019-1666). All authors contributed to this study. A.K.: investigation, methodology, validation, visualization, writing -original draft; A.S.: conceptualization, data curation, formal analysis, validation, visualization, writing -original draft; I.M.: resources, project administration; N.K.: investigation, methodology; A.G.: project administration, funding acquisition; Y.M.: conceptualization, supervision, validation, writing -review and editing; V.A.: resources, project administration, funding acquisition. All authors have read and agreed to the published version of the manuscript.
AUTHOR AFFILIATIONS 1 Department of Molecular Diagnostics and Epidemiology, Central Research Institute of Epidemiology, Moscow, Russia 2 Administrative and Management Department -Directorate, Central Research Institute of Epidemiology, Moscow, Russia 3 Republican Veterinary and Phytosanitary Laboratory Services Center, Yerevan, Armenia 4 Central Research Institute of Epidemiology, Moscow, Russia AUTHOR ORCIDs Anna Karpenko http://orcid.org/0000-0003-0486-1353 Andrey Shelenkov http://orcid.org/0000-0002-7409-077X diff --git a/grobid-trainer/resources/dataset/segmentation/corpus/tei/pub.1121876845.training.segmentation.tei.xml b/grobid-trainer/resources/dataset/segmentation/corpus/tei/pub.1121876845.training.segmentation.tei.xml index 2aaefa2251..4de9db70d6 100644 --- a/grobid-trainer/resources/dataset/segmentation/corpus/tei/pub.1121876845.training.segmentation.tei.xml +++ b/grobid-trainer/resources/dataset/segmentation/corpus/tei/pub.1121876845.training.segmentation.tei.xml @@ -4,9 +4,9 @@ - Iodocyclization in Aqueous Media and Supramolecular Reaction Control Using Water-Soluble Hosts Treyvon Bokoskie, † Christopher Cunningham, ‡ Cory Kornman, ‡ Tanay Kesharwani,* , ‡ and Mahesh Pattabiraman* , † Department of Chemistry, University of Nebraska Kearney, Kearney, Nebraska 68849, United States Department of Chemistry, University of West Florida, Pensacola, Florida 32514, United States * S Supporting Information ABSTRACT: Iodocyclization of 2-alkynylanisoles is an efficient route for synthesizing substituted benzofurans. Reaction efficiency with copper(II) sulfate and sodium iodide in an aqueous slurry under mild conditions is a manifold higher than in organic solvents. Water-soluble hosts of the cyclodextrin family solubilize the compounds in aqueous media and affect the reaction efficiency through conformation control and steric interactions. Computational chemistry and spectral titration provide information on the host-guest complex structure and insight into the mechanistic basis of the observed effects. + Iodocyclization in Aqueous Media and Supramolecular Reaction Control Using Water-Soluble Hosts Treyvon Bokoskie, † Christopher Cunningham, ‡ Cory Kornman, ‡ Tanay Kesharwani,* , ‡ and Mahesh Pattabiraman* , † Department of Chemistry, University of Nebraska Kearney, Kearney, Nebraska 68849, United States Department of Chemistry, University of West Florida, Pensacola, Florida 32514, United States * S Supporting Information ABSTRACT: Iodocyclization of 2-alkynylanisoles is an efficient route for synthesizing substituted benzofurans. Reaction efficiency with copper(II) sulfate and sodium iodide in an aqueous slurry under mild conditions is a manifold higher than in organic solvents. Water-soluble hosts of the cyclodextrin family solubilize the compounds in aqueous media and affect the reaction efficiency through conformation control and steric interactions. Computational chemistry and spectral titration provide information on the host-guest complex structure and insight into the mechanistic basis of the observed effects. - ■ INTRODUCTION Benzo[b]furans are frequently encountered structural cores in natural compounds 1-4 and bioactive molecules. 5-11 The significance of the benzofuran framework is evidenced from its ubiquity in plant products and prevalence as the central structures of several biomolecules, especially antimicro-bials, 12-14 analgesics, 15,16 and anti-inflammatory agents. 7,17 This biologically useful heterocyclic core structure is also part of several drug molecules (Figure 1). 6,18,19 Given its practical significance, there is strong justification for the development of new and efficient synthetic routes to access benzofurans, especially in an environmentally benign and sustainable manner. Currently, there are several synthetic routes reported in the synthetic organic chemistry literature for these compounds that report excellent reaction yields and selectivity. 13,14,20,21 However, there are very few reports on improving efficiency of these reactions in a sustainable manner consistent with the principles of green chemistry. We report a convenient and efficient method for the synthesis of substituted benzofurans through the iodocyclization reaction (Scheme 1) in an aqueous environment using economic, safe, and environmentally benign reagents (CuSO 4 and NaI) under mild/moderate conditions. In the aforementioned reaction condition, iodocyclization conversions are at least thrice higher than the reaction in a polar protic solvent such as ethanol. There have been no reports on the in situ generation of I 2 for iodocyclization of 2-alkynylanisoles and its efficiency in organic and aqueous media. This work features the unusual + ■ INTRODUCTION Benzo[b]furans are frequently encountered structural cores in natural compounds 1-4 and bioactive molecules. 5-11 The significance of the benzofuran framework is evidenced from its ubiquity in plant products and prevalence as the central structures of several biomolecules, especially antimicro-bials, 12-14 analgesics, 15,16 and anti-inflammatory agents. 7,17 This biologically useful heterocyclic core structure is also part of several drug molecules (Figure 1). 6,18,19 Given its practical significance, there is strong justification for the development of new and efficient synthetic routes to access benzofurans, especially in an environmentally benign and sustainable manner. Currently, there are several synthetic routes reported in the synthetic organic chemistry literature for these compounds that report excellent reaction yields and selectivity. 13,14,20,21 However, there are very few reports on improving efficiency of these reactions in a sustainable manner consistent with the principles of green chemistry. We report a convenient and efficient method for the synthesis of substituted benzofurans through the iodocyclization reaction (Scheme 1) in an aqueous environment using economic, safe, and environmentally benign reagents (CuSO 4 and NaI) under mild/moderate conditions. In the aforementioned reaction condition, iodocyclization conversions are at least thrice higher than the reaction in a polar protic solvent such as ethanol. There have been no reports on the in situ generation of I 2 for iodocyclization of 2-alkynylanisoles and its efficiency in organic and aqueous media. This work features the unusual Received: August 2, 2019 Accepted: October 3, 2019 Published: October 17, 2019 @@ -14,53 +14,57 @@ Article http://pubs.acs.org/journal/acsodf Cite This: ACS Omega 2019, 4, 17830-17836 © 2019 American Chemical Society 17830 DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 This is an open access article published under an ACS AuthorChoice License, which permits copying and redistribution of the article or any adaptations for non-commercial purposes. Downloaded via 37.168.2.205 on October 18, 2024 at 10:25:06 (UTC). See https://pubs.acs.org/sharingguidelines for options on how to legitimately share published articles. - phenomenon of an organic reaction in an aqueous slurry and the amenability of this reaction toward sustainable synthesis. Water-soluble hosts, such as cyclodextrins (CDs), calixar-enes, and micelles, have been often employed in influencing reaction rates of reactions in aqueous media; both increase (catalysis) and decrease (retardant) in reaction rates have been used to understand the characteristics of the reaction in the aqueous environment. Herein, we report our findings on the influence of cyclodextrin family on the iodocyclization reaction rates in an aqueous environment through encapsulation. Empirical findings of reaction rates coupled with spectral titration and computational investigations provide information about the structural aspects of the host-guest inclusion complex. In addition, the influence of hosts on the reaction rates has been studied in this work, which offers a unique insight into a previously unexplored mechanistic feature of the iodocyclization reaction. ■ EXPERIMENTAL SECTION The starting substrate, 1-methoxy-2-(phenylethynyl)benzene (1a), was prepared based on the previously reported procedure. 22 Stock solutions of the alkyne 1a in dichloro-methane and aqueous solutions of copper sulfate and sodium iodide (separately) were prepared in standard flasks. The volume corresponding to the required mass of the substrate was pipetted into a glass vial and the solvent was evaporated off. To the resulting neat substrate in the vial, the required volume of aqueous solution of reagents was dispensed, followed by water to bring the solution to a specific dilution. Typical concentrations of the experiment are 0.3 mmol of the substrate in 25 mL of the aqueous medium. The durations and temperature of the reaction are specified in Table 1. Following the reaction, the slurry was diluted with water and subject to biphasic extraction by stirring the solution with ethyl acetate for 5 h. The organic layer was isolated, the solvent removed in vacuo, and the residue from the reaction analyzed spectroscopically. The proportions of the product and reactant as well as conversions were calculated based on the integration of peak areas in the 1 H NMR spectra (Supporting Information) recorded on a 400 MHz Bruker AVANCE spectrometer. For the reaction in organic solvent, 0.3 mmol of alkyne was dissolved in 10 mL of an appropriate solvent followed by the addition of specific amounts of CuSO 4 •5H 2 O and NaI. Additional solvent was added such that the final volume was 25 mL. The reaction solutions were stirred at the temperatures and for the durations in Table 2. Following the reactions, ethyl alcohol was removed in vacuo. Residue water and ethyl acetate were added to separate the organic and the inorganic components. The organic layer was separated and evaporated in vacuo after which the products were dried under high vacuum and characterized by 1 H NMR spectroscopy. NMR titration was performed by obtaining a saturated solution of 1a in water by sonicating ∼7 mg of the compound in 2 mL D 2 O followed by removing the ppt through a syringe filter. Then, 0.6 mL of the filtered solution was subject to NMR titration with an addition of the powder form of cyclodextrin(s). Concentration of the saturated solution of 1a in water was sufficient enough to be observed in the spectrometer at with 64 scans. Computational chemistry of the reactant and its host-guest complexes with cyclodextrin was performed using Gaussian '09 software package. Structures of host-guest complexes were calculated using the ONIOM multilevel theory function in the software. The host molecules (CDs) were treated at the molecular mechanics level (UFF) and the guests were treated at the HF 6-31G basis set. Geometric optimizations and frequency calculations were performed in the gas phase. All normal mode frequencies of optimized structures were positive. ■ RESULTS AND DISCUSSION Iodocyclization Reaction. Mixtures of copper sulfate and sodium iodide generate molecular iodine (I 2 ) in situ, and the cyclization of 2-phenethynylanisole (1a) is initiated by the electrophilic interaction of I 2 with the alkyne. The mechanism of iodocyclization reaction is understood to proceed via the formation of a cyclic iodinium intermediate 3a (Scheme 2). 23-25 This electrophilic attack triggers the electrocyclization process involving nucleophilic assistance from the conforma-tionally predisposed ether functionality in the molecule. The Table 1. Extent of Iodocyclization of 1a in Aqueous Slurry time ratio (sub/reagent) a conv (%) b temp 24 h 1:1:1 33 25 °C 24 h 1:3:3 58 25 °C 24 h 1:5:5 92 25 °C 36 h 1:3:3 73 60 °C 48 h 1:3:3 81 60 °C a Quantities of reactants in 25 mL water: 0.3 mmol substrate, relative ratios of CuSO 4 , and NaI listed in table. b Conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. Table 2. Extent of Iodocyclization of 1a in Homogeneous Media system time ratio (sub/reagent) a conv (%) b temp methanol 24 h 1:3:3 14 25 °C 50% MeOH/H 2 O 24 h 1:3:3 45 25 °C ethanol 24 h 1:3:3 11 25 °C ethanol 60 h 1:5:5 52 25 °C ethanol 24 h 1:5:5 62 60 °C a Quantities of reactants in 25 mL of medium: 0.3 mmol substrate, relative ratios of CuSO 4 and NaI listed in table. b Conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. Scheme 2. Mechanism of Iodocyclization Reaction + phenomenon of an organic reaction in an aqueous slurry and the amenability of this reaction toward sustainable synthesis. Water-soluble hosts, such as cyclodextrins (CDs), calixar-enes, and micelles, have been often employed in influencing reaction rates of reactions in aqueous media; both increase (catalysis) and decrease (retardant) in reaction rates have been used to understand the characteristics of the reaction in the aqueous environment. Herein, we report our findings on the influence of cyclodextrin family on the iodocyclization reaction rates in an aqueous environment through encapsulation. Empirical findings of reaction rates coupled with spectral titration and computational investigations provide information about the structural aspects of the host-guest inclusion complex. In addition, the influence of hosts on the reaction rates has been studied in this work, which offers a unique insight into a previously unexplored mechanistic feature of the iodocyclization reaction. ■ EXPERIMENTAL SECTION The starting substrate, 1-methoxy-2-(phenylethynyl)benzene (1a), was prepared based on the previously reported procedure. 22 Stock solutions of the alkyne 1a in dichloro-methane and aqueous solutions of copper sulfate and sodium iodide (separately) were prepared in standard flasks. The volume corresponding to the required mass of the substrate was pipetted into a glass vial and the solvent was evaporated off. To the resulting neat substrate in the vial, the required volume of aqueous solution of reagents was dispensed, followed by water to bring the solution to a specific dilution. Typical concentrations of the experiment are 0.3 mmol of the substrate in 25 mL of the aqueous medium. The durations and temperature of the reaction are specified in Table 1. Following the reaction, the slurry was diluted with water and subject to biphasic extraction by stirring the solution with ethyl acetate for 5 h. The organic layer was isolated, the solvent removed in vacuo, and the residue from the reaction analyzed spectroscopically. The proportions of the product and reactant as well as conversions were calculated based on the integration of peak areas in the 1 H NMR spectra (Supporting Information) recorded on a 400 MHz Bruker AVANCE spectrometer. For the reaction in organic solvent, 0.3 mmol of alkyne was dissolved in 10 mL of an appropriate solvent followed by the addition of specific amounts of CuSO 4 •5H 2 O and NaI. Additional solvent was added such that the final volume was 25 mL. The reaction solutions were stirred at the temperatures and for the durations in Table 2. Following the reactions, ethyl alcohol was removed in vacuo. Residue water and ethyl acetate were added to separate the organic and the inorganic components. The organic layer was separated and evaporated in vacuo after which the products were dried under high vacuum and characterized by 1 H NMR spectroscopy. NMR titration was performed by obtaining a saturated solution of 1a in water by sonicating ∼7 mg of the compound in 2 mL D 2 O followed by removing the ppt through a syringe filter. Then, 0.6 mL of the filtered solution was subject to NMR titration with an addition of the powder form of cyclodextrin(s). Concentration of the saturated solution of 1a in water was sufficient enough to be observed in the spectrometer at with 64 scans. Computational chemistry of the reactant and its host-guest complexes with cyclodextrin was performed using Gaussian '09 software package. Structures of host-guest complexes were calculated using the ONIOM multilevel theory function in the software. The host molecules (CDs) were treated at the molecular mechanics level (UFF) and the guests were treated at the HF 6-31G basis set. Geometric optimizations and frequency calculations were performed in the gas phase. All normal mode frequencies of optimized structures were positive. ■ RESULTS AND DISCUSSION Iodocyclization Reaction. Mixtures of copper sulfate and sodium iodide generate molecular iodine (I 2 ) in situ, and the cyclization of 2-phenethynylanisole (1a) is initiated by the electrophilic interaction of I 2 with the alkyne. The mechanism of iodocyclization reaction is understood to proceed via the formation of a cyclic iodinium intermediate 3a (Scheme 2). 23-25 This electrophilic attack triggers the electrocyclization process involving nucleophilic assistance from the conforma-tionally predisposed ether functionality in the molecule. The Table 1. Extent of Iodocyclization of 1a in Aqueous Slurry time ratio (sub/reagent) a conv (%) b temp 24 h 1:1:1 33 25 °C 24 h 1:3:3 58 25 °C 24 h 1:5:5 92 25 °C 36 h 1:3:3 73 60 °C 48 h 1:3:3 81 60 °C a Quantities of reactants in 25 mL water: 0.3 mmol substrate, relative ratios of CuSO 4 , and NaI listed in table. b Conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. Table 2. Extent of Iodocyclization of 1a in Homogeneous Media system time ratio (sub/reagent) a conv (%) b temp methanol 24 h 1:3:3 14 25 °C 50% MeOH/H 2 O 24 h 1:3:3 45 25 °C ethanol 24 h 1:3:3 11 25 °C ethanol 60 h 1:5:5 52 25 °C ethanol 24 h 1:5:5 62 60 °C a Quantities of reactants in 25 mL of medium: 0.3 mmol substrate, relative ratios of CuSO 4 and NaI listed in table. b Conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. Scheme 2. Mechanism of Iodocyclization Reaction - ACS Omega Article + ACS Omega Article + + DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 - DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 + 17831 - 17831 + concomitant oxonium ion intermediate 4a reinstates its neutrality through the loss of the methyl group in the presence of the prospective counter-anion in the medium. Due to the involvement of an electrophilic attack in the first step and cationic intermediate that is in conjugation with aromatic rings, substituents with electronic effects greatly influence the reaction rates; electron donating groups increase the reaction rate, whereas electron withdrawing groups reduce the rate. Reaction in Homogeneous Aqueous Slurry and Organic Solvents. Results from the experiments performed at different reagent concentrations, temperatures, and durations are outlined in Table 1. It is evident that even though the reaction mixture was heterogeneous (the reagents and substrates were not in the same macrophase) significant conversion was realized. This was an intriguing finding, as the common knowledge in organic synthesis is that maximization of the reaction speed requires complete solubility of the reactants. While this finding was surprising, trends in the influence of physical factors on the extent of conversion were as expected; conversions increased progressively with time, with an increase in concentration of reagents, and at higher temperatures. The conditions employed in the slurry reactions presented in Table 1 are moderate. Near-quantitative conversion (greater than 90%) was achieved at room temperature and in the presence of 5 equiv of copper sulfate and sodium iodide for 24 h. Presence of slightly lesser amounts of reagents (3 equiv) still resulted in moderate conversions of around 50%. The extent of the reaction was significantly higher than that observed for the same reaction in organic media (vide infra). This observation provides an applied significance for our work due to its enhancement of the reaction rate as well as its green chemistry aspect; our work is now expected to be an example, among few others, where the reaction rate is higher in aqueous media compared to that in organic solvents. However, the most notable aspect of the experimental findings is that the reaction proceeds to a significant extent in an environmentally benign solvent, and that without the need of solubilizing agents such as surfactants or crown ethers. To gain perspective regarding the efficiency of the slurry reaction, we compared the iodocyclization conversions to those in traditional reaction conditions, such as a solution in the organic solvent. Hence the experimental conditions outlined above were employed, except in this case where alcoholic organic solvents were used. Table 2 lists the conversions achieved in various solvents and binary solvent mixtures. The reaction conversions were overall significantly lower than those observed using aqueous slurry conditions. The conversions in pure organic solvents at room temperatures were quite low, wherein for the same duration, the conversion in the slurry was at least five folds higher. Similarly, the conversions were many folds higher at elevated temperatures, as well as in the presence of increased equivalents of the reagents. A comparison of the data in Tables 1 and 2 clearly establishes the fact that the reaction proceeds with a higher rate and improved efficiency in the aqueous environment than in the organic solvent. Time-dependent reaction conversion experiment followed by NMR provides a clear perspective on the progress of the reaction (Figure S4, Supporting Information) where the ratio between proton signals of phenylene (2a) and the methoxy (1a) is proportional to reaction conversion. The importance of water in enhancing the reaction rate is evident from the second entry in Table 2, wherein a 50% v/v mixture of methanol in water was used as the reaction medium. The reaction conversion increased noticeably (about three times higher) and was comparable to that of the reaction in water. Supramolecular Influence on Reaction Rate. While solubility of the inorganic reagents in water increases, solubility of the substrate is starkly reduced. We hypothesized that increasing the solubility of the substrate, acting like a phase-transfer catalyst (PTC), might increase the reaction rate using solubilizing agents. Cavitands, especially cyclodextrins, have been used for this purpose. One specific example is the enhancement of the rate of cyclization of o-aminobenzamides due to its encapsulation reported by Wu et al. 26 It is especially relevant due to its structural similarity involving ring closure to form a five-membered benzofuran ring, in which the authors demonstrated the role of CDs acting as a PTC as well as a possible catalyst in stabilizing the reactant transition state. Expecting a similar effect in our reaction involving cyclization of an o-substituted substrate, we employed cyclodextrins to act as a PTC thereby increasing reaction rates (Figure 2). Three cavitands from the cyclodextrin family were used to solubilize the reactant in the aqueous environment (Figure 3). Cyclodextrins (CD) are bucket-shaped oligomeric structures composed of glucopyranose units (Figure 3, left). The hydroxyl groups of the gluropyranose on the circumference Figure 2. Encapsulation of aminobenzamides with ketones enhances cyclization through stabilization of the transition state. 26 Presence of a similar effect was explored in this iodocyclization cyclization of alkynyl anisoles. Figure 3. Chemical structure of cyclodextrins, its simplified topology, and 3-D rendering in a ball-and-stick model. - concomitant oxonium ion intermediate 4a reinstates its neutrality through the loss of the methyl group in the presence of the prospective counter-anion in the medium. Due to the involvement of an electrophilic attack in the first step and cationic intermediate that is in conjugation with aromatic rings, substituents with electronic effects greatly influence the reaction rates; electron donating groups increase the reaction rate, whereas electron withdrawing groups reduce the rate. Reaction in Homogeneous Aqueous Slurry and Organic Solvents. Results from the experiments performed at different reagent concentrations, temperatures, and durations are outlined in Table 1. It is evident that even though the reaction mixture was heterogeneous (the reagents and substrates were not in the same macrophase) significant conversion was realized. This was an intriguing finding, as the common knowledge in organic synthesis is that maximization of the reaction speed requires complete solubility of the reactants. While this finding was surprising, trends in the influence of physical factors on the extent of conversion were as expected; conversions increased progressively with time, with an increase in concentration of reagents, and at higher temperatures. The conditions employed in the slurry reactions presented in Table 1 are moderate. Near-quantitative conversion (greater than 90%) was achieved at room temperature and in the presence of 5 equiv of copper sulfate and sodium iodide for 24 h. Presence of slightly lesser amounts of reagents (3 equiv) still resulted in moderate conversions of around 50%. The extent of the reaction was significantly higher than that observed for the same reaction in organic media (vide infra). This observation provides an applied significance for our work due to its enhancement of the reaction rate as well as its green chemistry aspect; our work is now expected to be an example, among few others, where the reaction rate is higher in aqueous media compared to that in organic solvents. However, the most notable aspect of the experimental findings is that the reaction proceeds to a significant extent in an environmentally benign solvent, and that without the need of solubilizing agents such as surfactants or crown ethers. To gain perspective regarding the efficiency of the slurry reaction, we compared the iodocyclization conversions to those in traditional reaction conditions, such as a solution in the organic solvent. Hence the experimental conditions outlined above were employed, except in this case where alcoholic organic solvents were used. Table 2 lists the conversions achieved in various solvents and binary solvent mixtures. The reaction conversions were overall significantly lower than those observed using aqueous slurry conditions. The conversions in pure organic solvents at room temperatures were quite low, wherein for the same duration, the conversion in the slurry was at least five folds higher. Similarly, the conversions were many folds higher at elevated temperatures, as well as in the presence of increased equivalents of the reagents. A comparison of the data in Tables 1 and 2 clearly establishes the fact that the reaction proceeds with a higher rate and improved efficiency in the aqueous environment than in the organic solvent. Time-dependent reaction conversion experiment followed by NMR provides a clear perspective on the progress of the reaction (Figure S4, Supporting Information) where the ratio between proton signals of phenylene (2a) and the methoxy (1a) is proportional to reaction conversion. The importance of water in enhancing the reaction rate is evident from the second entry in Table 2, wherein a 50% v/v mixture of methanol in water was used as the reaction medium. The reaction conversion increased noticeably (about three times higher) and was comparable to that of the reaction in water. Supramolecular Influence on Reaction Rate. While solubility of the inorganic reagents in water increases, solubility of the substrate is starkly reduced. We hypothesized that increasing the solubility of the substrate, acting like a phase-transfer catalyst (PTC), might increase the reaction rate using solubilizing agents. Cavitands, especially cyclodextrins, have been used for this purpose. One specific example is the enhancement of the rate of cyclization of o-aminobenzamides due to its encapsulation reported by Wu et al. 26 It is especially relevant due to its structural similarity involving ring closure to form a five-membered benzofuran ring, in which the authors demonstrated the role of CDs acting as a PTC as well as a possible catalyst in stabilizing the reactant transition state. Expecting a similar effect in our reaction involving cyclization of an o-substituted substrate, we employed cyclodextrins to act as a PTC thereby increasing reaction rates (Figure 2). Three cavitands from the cyclodextrin family were used to solubilize the reactant in the aqueous environment (Figure 3). Cyclodextrins (CD) are bucket-shaped oligomeric structures composed of glucopyranose units (Figure 3, left). The hydroxyl groups of the gluropyranose on the circumference Figure 2. Encapsulation of aminobenzamides with ketones enhances cyclization through stabilization of the transition state. 26 Presence of a similar effect was explored in this iodocyclization cyclization of alkynyl anisoles. Figure 3. Chemical structure of cyclodextrins, its simplified topology, and 3-D rendering in a ball-and-stick model. + ACS Omega Article + + DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 - ACS Omega Article + 17832 - DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 + of the upper and lower rims of the CD render the molecule water-soluble, while the inner hydrophobic cavity encapsulates smaller organic compounds, such as the substrate (1), in water. The hexameric, heptameric, and octameric oligomer macro-cycles are termed α-, β-, γ-CD respectively. The electrocyclization was performed in aqueous under identical conditions at room temperature as discussed earlier in the presence of 3 equivalents of each CD oligomer (Table 3). Whereas, near quantitative conversion was achieved in an aqueous slurry reaction in 24 h, inclusion of substrate 1a within the smallest oligomer, α-CD, resulted in a 2.4 fold decrease in conversion. This was contradictory to the expected rate enhancement based on the originally hypothesized PTC advantage. Similar outcome was observed for the next larger oligomer β-CD, though the decrease in reaction rate was not as dramatic. The effect of the largest oligomer, γ-CD, continued in the same trend, except in this case an enhancement in reaction rate was observed compared to the slurry reaction. Near quantitative conversion was observed for γ-CD in less than 20 h, a significantly higher conversion than the corresponding reaction for water in 24 h. This suggested that the effect of CDs on the reaction rates were highly dependent on their cavity sizes suggesting a strong supramolecular control on the reaction mechanism as opposed to a simple PTC phenomenon. Computational Chemistry. We aimed to understand the effect of CDs on the reaction rates based on the computed geometry of inclusion complexes. Geometry-optimized struc-tures of reactants, products, and their complexes with β-cyclodextrin (all in gas phase) were studied. Initial analysis of the computational structures of the reactant 1a optimized in gas phase (HF 6-31G, Figure 4) and in an aqueous medium (SE PM6, Supporting Information) suggested that the molecule could adopt two possible conformations correspond-ing to a local minima: one in which the methyl group is pointed away from the alkyne group (conformation 1, C1), and the second in which the methyl group is pointed towards it (conformation 2, C2). Conformation 2 was less stable than conformation 1 in both levels of theory, perhaps due to the possible increased steric interaction between the methyl and alkynyl groups. Based on this information, we realized that our in silico studies should involve complexes of reactants with the CDs in C1 and C2 conformations as well. ΔΔ G G G stabilization nonreactive conf reactive conf (1) In the nonreacting conformation (C1), the methyl group is pointed perpendicular to the alkynyl moiety while in the reactive conformation (C2) it is pointed away, resulting in oxygen's lone pair predisposed for cyclization. The energies of geometry optimized structures of both conformations in the three CD hosts were performed in two-level ONIOM calculation with the lower level theory (MM, UFF) applied to host and the higher-level theory (HF-6-31G) applied to the guests. Geometry-optimized structures in the gas phase suggested that both phenyl and the anisole rings are conveniently encapsulated within the host cavities. For our analysis, we studied only structures in which the anisole ring is encapsulated as an influence on its conformation will have the most influence on its mechanism. Comparing the geometry-optimized structure of the reactant conformations C1 and C2 included within the cavitand provided a possible explanation for the observed change. For the unbound reactant, computational chemistry suggests that the preferred conformation is the reactive geometry, presumably due to coplanarity of lone pairs for conjugation. Frequency calculations on the geometry-optimized structures allowed us to evaluate the thermochemistry of the isomeric complex structures: C1@CD vs C2@CD (Figure 5). Comparison of the free energies of the complex formation showed that as the cavitand size increases the stability of reactive conformation decreases and that of the nonreactive conformation increases (Figure 6). If stabilization of the reactive geometry (due to oxygen predisposition) is the only factor, then α-CD would be the most reactive and γ-CD the least; however, experimentally this is not the case. Therefore, the second factor that would influence the reaction rate is the accessibility of the molecular iodine to the alkyne moiety to form the cyclic iodonium intermediate. Based on the analysis of complex structures it is evident that as the size of cavitand increases, the ability of iodine to react with the substrate would increase. While all CDs enhance the solubility of the substrate, the limited cavitand volume of α-CD also imposes a steric barrier on the I 2 -substrate interaction, which reduces reactivity. On the other hand, the larger cavity volume of γ-CD is able to simultaneously encapsulate the substrate and the reagent while also conferring the solubility advantage for the host without imposing a steric hindrance, which increases the reaction rate; the ability of γ-CD to form ternary complexes is well-documented in literature. Empirical Observation of Host-Guest Complex. Complex formation was experimentally ascertained through NMR host-guest titrations (Figure 7). Compound 1a is soluble enough in D 2 O (saturated solution) for 1 H NMR analysis. Addition of aliquots of β-and γ-CDs showed peak broadening indicating complexation. Surprisingly, there was no observable shift in signals, which is unusual. The extent of peak Table 3. Extent of Iodocyclization of 1a Complexed by Water-Soluble Hosts in the Presence of Three Equivalents of Host at 25 °C in the Presence of Five Equivalents of Reagents a system duration % conv α-CD 24 h 39 β-CD 12 h 66 β-CD 24 h 82 γ-CD 12 h 73 γ-CD 19 h > 95 a Quantities of reactants in 25 mL water: 0.3 mmol substrate, 1.5 mmol of CuSO 4 and NaI; conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. Figure 4. Geometry-optimized structures (Gaussian09, HF 6-31G) of the free guests starting at two different conformations: nonreacting (C1, left) and reacting (C2, right). - 17832 + ACS Omega Article - of the upper and lower rims of the CD render the molecule water-soluble, while the inner hydrophobic cavity encapsulates smaller organic compounds, such as the substrate (1), in water. The hexameric, heptameric, and octameric oligomer macro-cycles are termed α-, β-, γ-CD respectively. The electrocyclization was performed in aqueous under identical conditions at room temperature as discussed earlier in the presence of 3 equivalents of each CD oligomer (Table 3). Whereas, near quantitative conversion was achieved in an aqueous slurry reaction in 24 h, inclusion of substrate 1a within the smallest oligomer, α-CD, resulted in a 2.4 fold decrease in conversion. This was contradictory to the expected rate enhancement based on the originally hypothesized PTC advantage. Similar outcome was observed for the next larger oligomer β-CD, though the decrease in reaction rate was not as dramatic. The effect of the largest oligomer, γ-CD, continued in the same trend, except in this case an enhancement in reaction rate was observed compared to the slurry reaction. Near quantitative conversion was observed for γ-CD in less than 20 h, a significantly higher conversion than the corresponding reaction for water in 24 h. This suggested that the effect of CDs on the reaction rates were highly dependent on their cavity sizes suggesting a strong supramolecular control on the reaction mechanism as opposed to a simple PTC phenomenon. Computational Chemistry. We aimed to understand the effect of CDs on the reaction rates based on the computed geometry of inclusion complexes. Geometry-optimized struc-tures of reactants, products, and their complexes with β-cyclodextrin (all in gas phase) were studied. Initial analysis of the computational structures of the reactant 1a optimized in gas phase (HF 6-31G, Figure 4) and in an aqueous medium (SE PM6, Supporting Information) suggested that the molecule could adopt two possible conformations correspond-ing to a local minima: one in which the methyl group is pointed away from the alkyne group (conformation 1, C1), and the second in which the methyl group is pointed towards it (conformation 2, C2). Conformation 2 was less stable than conformation 1 in both levels of theory, perhaps due to the possible increased steric interaction between the methyl and alkynyl groups. Based on this information, we realized that our in silico studies should involve complexes of reactants with the CDs in C1 and C2 conformations as well. ΔΔ G G G stabilization nonreactive conf reactive conf (1) In the nonreacting conformation (C1), the methyl group is pointed perpendicular to the alkynyl moiety while in the reactive conformation (C2) it is pointed away, resulting in oxygen's lone pair predisposed for cyclization. The energies of geometry optimized structures of both conformations in the three CD hosts were performed in two-level ONIOM calculation with the lower level theory (MM, UFF) applied to host and the higher-level theory (HF-6-31G) applied to the guests. Geometry-optimized structures in the gas phase suggested that both phenyl and the anisole rings are conveniently encapsulated within the host cavities. For our analysis, we studied only structures in which the anisole ring is encapsulated as an influence on its conformation will have the most influence on its mechanism. Comparing the geometry-optimized structure of the reactant conformations C1 and C2 included within the cavitand provided a possible explanation for the observed change. For the unbound reactant, computational chemistry suggests that the preferred conformation is the reactive geometry, presumably due to coplanarity of lone pairs for conjugation. Frequency calculations on the geometry-optimized structures allowed us to evaluate the thermochemistry of the isomeric complex structures: C1@CD vs C2@CD (Figure 5). Comparison of the free energies of the complex formation showed that as the cavitand size increases the stability of reactive conformation decreases and that of the nonreactive conformation increases (Figure 6). If stabilization of the reactive geometry (due to oxygen predisposition) is the only factor, then α-CD would be the most reactive and γ-CD the least; however, experimentally this is not the case. Therefore, the second factor that would influence the reaction rate is the accessibility of the molecular iodine to the alkyne moiety to form the cyclic iodonium intermediate. Based on the analysis of complex structures it is evident that as the size of cavitand increases, the ability of iodine to react with the substrate would increase. While all CDs enhance the solubility of the substrate, the limited cavitand volume of α-CD also imposes a steric barrier on the I 2 -substrate interaction, which reduces reactivity. On the other hand, the larger cavity volume of γ-CD is able to simultaneously encapsulate the substrate and the reagent while also conferring the solubility advantage for the host without imposing a steric hindrance, which increases the reaction rate; the ability of γ-CD to form ternary complexes is well-documented in literature. Empirical Observation of Host-Guest Complex. Complex formation was experimentally ascertained through NMR host-guest titrations (Figure 7). Compound 1a is soluble enough in D 2 O (saturated solution) for 1 H NMR analysis. Addition of aliquots of β-and γ-CDs showed peak broadening indicating complexation. Surprisingly, there was no observable shift in signals, which is unusual. The extent of peak Table 3. Extent of Iodocyclization of 1a Complexed by Water-Soluble Hosts in the Presence of Three Equivalents of Host at 25 °C in the Presence of Five Equivalents of Reagents a system duration % conv α-CD 24 h 39 β-CD 12 h 66 β-CD 24 h 82 γ-CD 12 h 73 γ-CD 19 h > 95 a Quantities of reactants in 25 mL water: 0.3 mmol substrate, 1.5 mmol of CuSO 4 and NaI; conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. Figure 4. Geometry-optimized structures (Gaussian09, HF 6-31G) of the free guests starting at two different conformations: nonreacting (C1, left) and reacting (C2, right). + DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 - ACS Omega Article + 17833 - DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 + broadening was significant for γ-CD even at 1 equivalent, while it was minimal (though noticeable) for β-CD. The extent of peak broadening was similar for all nine aromatic protons, suggesting complexation of the host to both the phenyl and phenoxy sides. The presence of a single set of peaks indicated complexation kinetics faster than the NMR time scale, consistent with a weak complexation dynamic typically observed for CDs in general. Complexation of the guest to CDs was further ascertained through UV-vis and fluorometric titrations (section D, Supporting Information). UV-vis titration of 1a with β-CD showed increase in extinction coefficient of the chromophore (absorbance increase) with each addition. Similarly, there was a significant decrease in fluorescence of the chromophore in the presence of the host compared to that of the free guest. Spectral analysis of guest 1a in the presence and absence of water-soluble hosts indicated inclusion complex formation, which considered along with the NMR titration experiments, confirmed inclusion of the guest within the cavitand. Therefore, the changes in reaction conversion that we observed in our experiments were evidently the result of supramolecular (weak) interactions between the host and guest. Figure 5. Geometry-optimized of host-guest complex of 1a bound to CDs and relative stabilities based on free energies of formation as deduced from eq 1. Figure 6. Chart showing the trend in stabilization energy of the nonreacting conformer (ΔΔG stabilization eq 1, maroon, left axis) and its correlation with experimental reaction conversion (green, right axis). Figure 7. Partial 1 H NMR spectra of the saturated solution of 1a in D 2 O (top) and its complexes with two equivalents of β-CD (middle) and γ-CD (bottom). - 17833 + ACS Omega Article - broadening was significant for γ-CD even at 1 equivalent, while it was minimal (though noticeable) for β-CD. The extent of peak broadening was similar for all nine aromatic protons, suggesting complexation of the host to both the phenyl and phenoxy sides. The presence of a single set of peaks indicated complexation kinetics faster than the NMR time scale, consistent with a weak complexation dynamic typically observed for CDs in general. Complexation of the guest to CDs was further ascertained through UV-vis and fluorometric titrations (section D, Supporting Information). UV-vis titration of 1a with β-CD showed increase in extinction coefficient of the chromophore (absorbance increase) with each addition. Similarly, there was a significant decrease in fluorescence of the chromophore in the presence of the host compared to that of the free guest. Spectral analysis of guest 1a in the presence and absence of water-soluble hosts indicated inclusion complex formation, which considered along with the NMR titration experiments, confirmed inclusion of the guest within the cavitand. Therefore, the changes in reaction conversion that we observed in our experiments were evidently the result of supramolecular (weak) interactions between the host and guest. Figure 5. Geometry-optimized of host-guest complex of 1a bound to CDs and relative stabilities based on free energies of formation as deduced from eq 1. Figure 6. Chart showing the trend in stabilization energy of the nonreacting conformer (ΔΔG stabilization eq 1, maroon, left axis) and its correlation with experimental reaction conversion (green, right axis). Figure 7. Partial 1 H NMR spectra of the saturated solution of 1a in D 2 O (top) and its complexes with two equivalents of β-CD (middle) and γ-CD (bottom). + DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 - ACS Omega Article + 17834 - DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 + Effect of Substituents. The effect of substituents on the reaction outcome, performed under the reported conditions, was explored. Two additional substrates were used, namely 4-methoxy-and a 4-cyano-substituted derivatives. As iodocycli-zation involves a cationic iodonium intermediate, it is expected that electronically activated substrates would enhance the reaction rate and vice versa. The 4-methoxy derivative of 1a underwent near quantitative conversion in 20 h under unmediated conditions, while the 4-cyano derivative resulted in no significant conversion under similar conditions (Table 4). These results were consistent with expectations. Similar to the experiments with 1a, the reaction was performed in the presence of CDs. Consistent with the earlier findings, the reaction conversions were enhanced for all substrates, substantiating our hypothesis that the complexation of substrates to CDs increases interaction between I 2 and the alkynyl bond along with PTC effect. ■ CONCLUSIONS This work reports enhancement of the iodocyclization reaction of 1-alkoxyphenyl-2-phenyl acetylene in the presence of copper sulfate and sodium iodide to yield the corresponding benzofuran. The reaction has been observed to proceed faster in an aqueous environment as a homogeneous slurry than in the solution in organic solvents. We speculate that this is due to the increased solubility of the inorganic reagents in water leading to an increase in the local concentration of the reactants and reagents. High reaction conversions were achieved under moderate conditions in an environmentally friendly solvent. We attempted to improve the reaction conversions by utilizing solubilizers to enhance the aqueous solubility of the substrate, which yielded mixed results: the large host γ-CD enhanced reaction rate compared to the aq slurry while the smaller hosts showing reduced rates exhibiting a clear size-dependent trend. Energy-minimized structures of the reactant and the complex suggested that the gradation in reaction rates is due to the differential stabilization of two different conformations (reactive and nonreactive) of the substrate. While all three hosts increase solubility of the substrate in water, the smaller hosts also prevent their reactivity through steric hinderance; the larger cavity volume of γ-CD does not impose such physical limitation, which results in an overall rate enhancement. - 17834 +
■ ASSOCIATED CONTENT * S Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsome-ga.9b02466. Synthesis of substrates, time-dependent conversion, computational chemistry details, and UV/Fluorescence spectra (PDF)
- Effect of Substituents. The effect of substituents on the reaction outcome, performed under the reported conditions, was explored. Two additional substrates were used, namely 4-methoxy-and a 4-cyano-substituted derivatives. As iodocycli-zation involves a cationic iodonium intermediate, it is expected that electronically activated substrates would enhance the reaction rate and vice versa. The 4-methoxy derivative of 1a underwent near quantitative conversion in 20 h under unmediated conditions, while the 4-cyano derivative resulted in no significant conversion under similar conditions (Table 4). These results were consistent with expectations. Similar to the experiments with 1a, the reaction was performed in the presence of CDs. Consistent with the earlier findings, the reaction conversions were enhanced for all substrates, substantiating our hypothesis that the complexation of substrates to CDs increases interaction between I 2 and the alkynyl bond along with PTC effect. ■ CONCLUSIONS This work reports enhancement of the iodocyclization reaction of 1-alkoxyphenyl-2-phenyl acetylene in the presence of copper sulfate and sodium iodide to yield the corresponding benzofuran. The reaction has been observed to proceed faster in an aqueous environment as a homogeneous slurry than in the solution in organic solvents. We speculate that this is due to the increased solubility of the inorganic reagents in water leading to an increase in the local concentration of the reactants and reagents. High reaction conversions were achieved under moderate conditions in an environmentally friendly solvent. We attempted to improve the reaction conversions by utilizing solubilizers to enhance the aqueous solubility of the substrate, which yielded mixed results: the large host γ-CD enhanced reaction rate compared to the aq slurry while the smaller hosts showing reduced rates exhibiting a clear size-dependent trend. Energy-minimized structures of the reactant and the complex suggested that the gradation in reaction rates is due to the differential stabilization of two different conformations (reactive and nonreactive) of the substrate. While all three hosts increase solubility of the substrate in water, the smaller hosts also prevent their reactivity through steric hinderance; the larger cavity volume of γ-CD does not impose such physical limitation, which results in an overall rate enhancement. ■ ASSOCIATED CONTENT * S Supporting Information The Supporting Information is available free of charge on the ACS Publications website at DOI: 10.1021/acsome-ga.9b02466. Synthesis of substrates, time-dependent conversion, computational chemistry details, and UV/Fluorescence spectra (PDF) ■ AUTHOR INFORMATION Corresponding Authors *E-mail: tkesharwani@uwf.edu (T.K.). *E-mail: pattabiramm2@unk.edu (M.P.). ORCID Tanay Kesharwani: 0000-0001-8193-0004 Mahesh Pattabiraman: 0000-0002-6763-6711 Notes + ■ AUTHOR INFORMATION Corresponding Authors *E-mail: tkesharwani@uwf.edu (T.K.). *E-mail: pattabiramm2@unk.edu (M.P.). ORCID Tanay Kesharwani: 0000-0001-8193-0004 Mahesh Pattabiraman: 0000-0002-6763-6711 Notes The authors declare no competing financial interest. -
The authors declare no competing financial interest. ■ ACKNOWLEDGMENTS This research was supported by the ACS-Petroleum Research Fund (#54862-UR4) and the Research Corporation for Science Advancement for the Cottrell College Science Award (ID 23248). M.P. is thankful for the support from the UNK's Office of Sponsored Programs. T.K. and C.C. are grateful for generous support provided by the University of West Florida (UWF), the UWF's Office of Research and Sponsored Programs and Office of Undergraduate Research. C.C. is thankful to the National Institute of General Medical Sciences of the National Institutes of Health under grant no. 1T34GM110517-01. This content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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■ ACKNOWLEDGMENTS This research was supported by the ACS-Petroleum Research Fund (#54862-UR4) and the Research Corporation for Science Advancement for the Cottrell College Science Award (ID 23248). M.P. is thankful for the support from the UNK's Office of Sponsored Programs. T.K. and C.C. are grateful for generous support provided by the University of West Florida (UWF), the UWF's Office of Research and Sponsored Programs and Office of Undergraduate Research. C.C. is thankful to the National Institute of General Medical Sciences of the National Institutes of Health under grant no. 1T34GM110517-01. This content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
- ■ REFERENCES (1) Chand, K.; Rajeshwari; Hiremathad, A.; Singh, M.; Santos, M. A.; Keri, R. S. A review on antioxidant potential of bioactive heterocycle benzofuran: Natural and synthetic derivatives. Pharmacol. Rep. 2017, 69, 281-295. (2) Kuramochi, K.; Tsubaki, K. Synthesis and structural character-ization of natural benzofuranoids. J. Nat. Prod. 2015, 78, 1056-1066. (3) Reddy, V. K.; Rao, J. V.; Reddy, L. B.; Ram, B.; Balram, B. Synthesis and antibacterial activity of 4,6-dimethoxy-2-(4-methoxyphenyl)benzofuran-3-yl-methanone derivatives and its inter-mediates. Asian J. Chem. 2015, 27, 2245-2248. (4) Heravi, M. M.; Zadsirjan, V.; Hamidi, H.; Tabar Amiri, P. H. Total synthesis of natural products containing benzofuran rings. RSC Adv. 2017, 7, 24470-24521. (5) Dixit, M.; Tripathi, B. K.; Tamrakar, A. K.; Srivastava, A. K.; Kumar, B.; Goel, A. Synthesis of benzofuran scaffold-based potential PTP-1B inhibitors. Bioorg. Med. Chem. 2007, 15, 727-734. (6) Khanam, H.; Shamsuzzaman. Bioactive Benzofuran derivatives: A review. Eur. J. Med. Chem. 2015, 97, 483-504. (7) Naik, R.; Harmalkar, D. S.; Xu, X.; Jang, K.; Lee, K. Bioactive benzofuran derivatives: moracins A-Z in medicinal chemistry. Eur. J. Med. Chem. 2015, 90, 379-393. (8) Radadiya, A.; Shah, A. Bioactive benzofuran derivatives: An insight on lead developments, radioligands and advances of the last decade. Eur. J. Med. Chem. 2015, 97, 356-376. (9) Rizzo, S.; Rivieŕe, C.; Piazzi, L.; Bisi, A.; Gobbi, S.; Bartolini, M.; Andrisano, V.; Morroni, F.; Tarozzi, A.; Monti, J.-P.; Rampa, A. Benzofuran-based hybrid compounds for the inhibition of cholines-terase activity, β amyloid aggregation, and aβ neurotoxicity. J. Med. Chem. 2008, 51, 2883-2886. (10) Kirilmis, C.; Ahmedzade, M.; Servi, S.; Koca, M.; Kizirgil, A.; Kazaz, C. Synthesis and antimicrobial activity of some novel derivatives of benzofuran: part 2. The synthesis and antimicrobial activity of some novel 1-(1-benzofuran-2-yl)-2-mesitylethanone derivatives. Eur. J. Med. Chem. 2008, 43, 300-308. + ■ REFERENCES (1) Chand, K.; Rajeshwari; Hiremathad, A.; Singh, M.; Santos, M. A.; Keri, R. S. A review on antioxidant potential of bioactive heterocycle benzofuran: Natural and synthetic derivatives. Pharmacol. Rep. 2017, 69, 281-295. (2) Kuramochi, K.; Tsubaki, K. Synthesis and structural character-ization of natural benzofuranoids. J. Nat. Prod. 2015, 78, 1056-1066. (3) Reddy, V. K.; Rao, J. V.; Reddy, L. B.; Ram, B.; Balram, B. Synthesis and antibacterial activity of 4,6-dimethoxy-2-(4-methoxyphenyl)benzofuran-3-yl-methanone derivatives and its inter-mediates. Asian J. Chem. 2015, 27, 2245-2248. (4) Heravi, M. M.; Zadsirjan, V.; Hamidi, H.; Tabar Amiri, P. H. Total synthesis of natural products containing benzofuran rings. RSC Adv. 2017, 7, 24470-24521. (5) Dixit, M.; Tripathi, B. K.; Tamrakar, A. K.; Srivastava, A. K.; Kumar, B.; Goel, A. Synthesis of benzofuran scaffold-based potential PTP-1B inhibitors. Bioorg. Med. Chem. 2007, 15, 727-734. (6) Khanam, H.; Shamsuzzaman. Bioactive Benzofuran derivatives: A review. Eur. J. Med. Chem. 2015, 97, 483-504. (7) Naik, R.; Harmalkar, D. S.; Xu, X.; Jang, K.; Lee, K. Bioactive benzofuran derivatives: moracins A-Z in medicinal chemistry. Eur. J. Med. Chem. 2015, 90, 379-393. (8) Radadiya, A.; Shah, A. Bioactive benzofuran derivatives: An insight on lead developments, radioligands and advances of the last decade. Eur. J. Med. Chem. 2015, 97, 356-376. (9) Rizzo, S.; Rivieŕe, C.; Piazzi, L.; Bisi, A.; Gobbi, S.; Bartolini, M.; Andrisano, V.; Morroni, F.; Tarozzi, A.; Monti, J.-P.; Rampa, A. Benzofuran-based hybrid compounds for the inhibition of cholines-terase activity, β amyloid aggregation, and aβ neurotoxicity. J. Med. Chem. 2008, 51, 2883-2886. (10) Kirilmis, C.; Ahmedzade, M.; Servi, S.; Koca, M.; Kizirgil, A.; Kazaz, C. Synthesis and antimicrobial activity of some novel derivatives of benzofuran: part 2. The synthesis and antimicrobial activity of some novel 1-(1-benzofuran-2-yl)-2-mesitylethanone derivatives. Eur. J. Med. Chem. 2008, 43, 300-308. - Table 4. Substituent Effect on Extent of Reaction in Presence and Absence of Macrocyclic Cavitand a R time conv (%) water γ-CD 4-H (1a) 20 h 81 >95 4-OCH 3 (1b) 20 h 95 >95 4-CN(1c) 3 6 h 1 1 a Quantities of reactants in 25 mL water: 0.3 mmol substrate, in the presence of five equivalents of reagents and three equivalents of host; conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. + Table 4. Substituent Effect on Extent of Reaction in Presence and Absence of Macrocyclic Cavitand a R time conv (%) water γ-CD 4-H (1a) 20 h 81 >95 4-OCH 3 (1b) 20 h 95 >95 4-CN(1c) 3 6 h 1 1 a Quantities of reactants in 25 mL water: 0.3 mmol substrate, in the presence of five equivalents of reagents and three equivalents of host; conversions are the average of three independent, but simultaneous, trials that yield standard deviations less than 5%. - ACS Omega Article + ACS Omega Article - DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 + DOI: 10.1021/acsomega.9b02466 ACS Omega 2019, 4, 17830-17836 - 17835 + 17835 - (11) Koca, M.; Servi, S.; Kirilmis, C.; Ahmedzade, M.; Kazaz, C.; O ̈zbek, B.; O ̈tuk, G. Synthesis and antimicrobial activity of some novel derivatives of benzofuran: part 1. Synthesis and antimicrobial activity of (benzofuran-2-yl)(3-phenyl-3-methylcyclobutyl) ketoxime derivatives. Eur. J. Med. Chem. 2005, 40, 1351-1358. (12) Hiremathad, A.; Patil, M. R.; Chethana, K. R.; Chand, K.; Santos, M. A.; Keri, R. S. Benzofuran: an emerging scaffold for antimicrobial agents. RSC Adv. 2015, 5, 96809-96828. (13) Jiang, X.; Liu, W.; Zhang, W.; Jiang, F.; Gao, Z.; Zhuang, H.; Fu, L. Synthesis and antimicrobial evaluation of new benzofuran derivatives. Eur. J. Med. Chem. 2011, 46, 3526-3530. (14) Zhang, W.; Liu, W.; Jiang, X.; Jiang, F.; Zhuang, H.; Fu, L. Design, synthesis and antimicrobial activity of chiral 2-(substituted-hydroxyl)-3-(benzo[d]oxazol-5-yl)propanoic acid derivatives. Eur. J. Med. Chem. 2011, 46, 3639-3650. (15) El-Sawy, E. R.; Ebaid, M. S.; Abo-Salem, H. M.; El-Hallouty, S.; Kassem, E. M.; Mandour, A. H. Synthesis and biological activity of novel series of 4-methoxy, and 4,9-dimethoxy-5-substituted furo[2,3-g]-1,2,3-benzoxathiazine-7,7-dioxide derivatives. J. Adv. Res. 2014, 5, 337-346. (16) Boyle, E. A.; Mangan, F. R.; Markwell, R. E.; Smith, S. A.; Thomson, M. J.; Ward, R. W.; Wyman, P. A. 7-Aroyl-2,3-dihydrobenzo[b]furan-3-carboxylic acids and 7-benzoyl-2,3-dihydrobenzo[b]thiophene-3-carboxylic acids as analgesic agents. J. Med. Chem. 1986, 29, 894-898. (17) Dawood, K. M. Benzofuran derivatives: a patent review. Expert Opin. Ther. Pat. 2013, 23, 1133-1156. (18) Goyal, D.; Kaur, A.; Goyal, B. Benzofuran and Indole: Promising Scaffolds for Drug Development in Alzheimer's Disease. ChemMedChem 2018, 13, 1275-1299. (19) Nevagi, R. J.; Dighe, S. N.; Dighe, S. N. Biological and medicinal significance of benzofuran. Eur. J. Med. Chem. 2015, 97, 561-581. (20) Heravi, M. M.; Zadsirjan, V. Recent advances in the synthesis of benzo[b]furans. Adv. Heterocycl. Chem. 2015, 117, 261-376. (21) Kwiecien, H.; Smist, M.; Kowalewska, M. Recent development on the synthesis of benzo[b]-and naphtho[b]furans: a review. Curr. Org. Synth. 2012, 9, 529-560. (22) Yue, D.; Yao, T.; Larock, R. C. Synthesis of 2,3-disubstituted benzo[b]furans by the palladium-catalyzed coupling of o-iodoanisoles and terminal alkynes, followed by electrophilic cyclization. J. Org. Chem. 2005, 70, 10292-10296. (23) Kim, S.; Dahal, N.; Kesharwani, T. Environmentally benign process for the synthesis of 2,3-disubstituted benzo[b]thiophenes using electrophilic cyclization. Tetrahedron Lett. 2013, 54, 4373-4376. (24) Kesharwani, T.; Worlikar, S. A.; Larock, R. C. Synthesis of 2,3-Disubstituted Benzo[b]selenophenes via Electrophilic Cyclization. J. Org. Chem. 2006, 71, 2307-2312. (25) Kesharwani, T.; Kornman, C.; Tonnaer, A.; Hayes, A.; Kim, S.; Dahal, N.; Romero, R.; Royappa, A. Sodium halides as the source of electrophilic halogens in green synthesis of 3-halo-and 3,n-dihalobenzo[b]thiophenes. Tetrahedron 2018, 74, 2973-2984. (26) Wu, J.; Du, X.; Ma, J.; Zhang, Y.; Shi, Q.; Luo, L.; Song, B.; Yang, S.; Hu, D. Preparation of 2,3-dihydroquinazolin-4(1H)-one derivatives in aqueous media with β-cyclodextrin-SO3H as a recyclable catalyst. Green Chem. 2014, 16, 3210-3217. + (11) Koca, M.; Servi, S.; Kirilmis, C.; Ahmedzade, M.; Kazaz, C.; O ̈zbek, B.; O ̈tuk, G. Synthesis and antimicrobial activity of some novel derivatives of benzofuran: part 1. Synthesis and antimicrobial activity of (benzofuran-2-yl)(3-phenyl-3-methylcyclobutyl) ketoxime derivatives. Eur. J. Med. Chem. 2005, 40, 1351-1358. (12) Hiremathad, A.; Patil, M. R.; Chethana, K. R.; Chand, K.; Santos, M. A.; Keri, R. S. Benzofuran: an emerging scaffold for antimicrobial agents. RSC Adv. 2015, 5, 96809-96828. (13) Jiang, X.; Liu, W.; Zhang, W.; Jiang, F.; Gao, Z.; Zhuang, H.; Fu, L. Synthesis and antimicrobial evaluation of new benzofuran derivatives. Eur. J. Med. Chem. 2011, 46, 3526-3530. (14) Zhang, W.; Liu, W.; Jiang, X.; Jiang, F.; Zhuang, H.; Fu, L. Design, synthesis and antimicrobial activity of chiral 2-(substituted-hydroxyl)-3-(benzo[d]oxazol-5-yl)propanoic acid derivatives. Eur. J. Med. Chem. 2011, 46, 3639-3650. (15) El-Sawy, E. R.; Ebaid, M. S.; Abo-Salem, H. M.; El-Hallouty, S.; Kassem, E. M.; Mandour, A. H. Synthesis and biological activity of novel series of 4-methoxy, and 4,9-dimethoxy-5-substituted furo[2,3-g]-1,2,3-benzoxathiazine-7,7-dioxide derivatives. J. Adv. Res. 2014, 5, 337-346. (16) Boyle, E. A.; Mangan, F. R.; Markwell, R. E.; Smith, S. A.; Thomson, M. J.; Ward, R. W.; Wyman, P. A. 7-Aroyl-2,3-dihydrobenzo[b]furan-3-carboxylic acids and 7-benzoyl-2,3-dihydrobenzo[b]thiophene-3-carboxylic acids as analgesic agents. J. Med. Chem. 1986, 29, 894-898. (17) Dawood, K. M. Benzofuran derivatives: a patent review. Expert Opin. Ther. Pat. 2013, 23, 1133-1156. (18) Goyal, D.; Kaur, A.; Goyal, B. Benzofuran and Indole: Promising Scaffolds for Drug Development in Alzheimer's Disease. ChemMedChem 2018, 13, 1275-1299. (19) Nevagi, R. J.; Dighe, S. N.; Dighe, S. N. Biological and medicinal significance of benzofuran. Eur. J. Med. Chem. 2015, 97, 561-581. (20) Heravi, M. M.; Zadsirjan, V. Recent advances in the synthesis of benzo[b]furans. Adv. Heterocycl. Chem. 2015, 117, 261-376. (21) Kwiecien, H.; Smist, M.; Kowalewska, M. Recent development on the synthesis of benzo[b]-and naphtho[b]furans: a review. Curr. Org. Synth. 2012, 9, 529-560. (22) Yue, D.; Yao, T.; Larock, R. C. Synthesis of 2,3-disubstituted benzo[b]furans by the palladium-catalyzed coupling of o-iodoanisoles and terminal alkynes, followed by electrophilic cyclization. J. Org. Chem. 2005, 70, 10292-10296. (23) Kim, S.; Dahal, N.; Kesharwani, T. Environmentally benign process for the synthesis of 2,3-disubstituted benzo[b]thiophenes using electrophilic cyclization. Tetrahedron Lett. 2013, 54, 4373-4376. (24) Kesharwani, T.; Worlikar, S. A.; Larock, R. C. Synthesis of 2,3-Disubstituted Benzo[b]selenophenes via Electrophilic Cyclization. J. Org. Chem. 2006, 71, 2307-2312. (25) Kesharwani, T.; Kornman, C.; Tonnaer, A.; Hayes, A.; Kim, S.; Dahal, N.; Romero, R.; Royappa, A. Sodium halides as the source of electrophilic halogens in green synthesis of 3-halo-and 3,n-dihalobenzo[b]thiophenes. Tetrahedron 2018, 74, 2973-2984. (26) Wu, J.; Du, X.; Ma, J.; Zhang, Y.; Shi, Q.; Luo, L.; Song, B.; Yang, S.; Hu, D. Preparation of 2,3-dihydroquinazolin-4(1H)-one derivatives in aqueous media with β-cyclodextrin-SO3H as a recyclable catalyst. Green Chem. 2014, 16, 3210-3217. ACS Omega Article diff --git a/grobid-trainer/resources/dataset/segmentation/corpus/tei/s41588-024-01785-9.training.segmentation.tei.xml b/grobid-trainer/resources/dataset/segmentation/corpus/tei/s41588-024-01785-9.training.segmentation.tei.xml index f96b2ed5ba..306826a297 100644 --- a/grobid-trainer/resources/dataset/segmentation/corpus/tei/s41588-024-01785-9.training.segmentation.tei.xml +++ b/grobid-trainer/resources/dataset/segmentation/corpus/tei/s41588-024-01785-9.training.segmentation.tei.xml @@ -154,9 +154,11 @@ a) c) b) d) TP53 RB1 KRAS LRRC4C AKAP9 PKHD1L1 ANK1 BCL7A CDH10 PDGFRA PREX2 Lung-LargeCell (Oncogenic) 0 5 10 15 Clonal (NA) Clonal (early) Clonal (late) Subclonal NA NF2 AKT1 KLF4 PIK3CA SMARCB1 SMO USP17L22 ATM TRAF7 ZSCAN5A CNS-Menin (Oncogenic) 0 5 10 15 Clonal (NA) Clonal (early) Clonal (late) Subclonal NA KIT KRAS MUC20 NRAS RAC1 BIRC6 KLF4 EP300 SPEN Testis-GCT (Oncogenic) 0 2 4 6 8 10 Clonal (NA) Clonal (early) Clonal (late) Subclonal NA IDH1 CIC FUBP1 NIPBL NOTCH1 IDH2 TCF12 ARID1A PIK3CA SMARCA4 ZBTB20 ATRX BCOR PBRM1 CNS-Oligo (Oncogenic) 0 10 20 30 40 Clonal (NA) Clonal (early) Clonal (late) Subclonal NA Extended Data Fig. 8 | Oncogenic clonal and subclonal mutations across candidate driver genes. Oncogenic clonal and subclonal mutations across candidate driver genes in: a) Meningioma; b) Large cell lung cancer; c) Testicular germ cell tumour; d) Oligodendroglioma. - Nature Genetics Article + Nature Genetics + + Article https://doi.org/10.1038/s41588-024-01785-9 -
https://doi.org/10.1038/s41588-024-01785-9 RUNX1 IFNG PRKCD ASXL1 APC HNF4A PRKCI HDAC6 CDK1 HLA-B BTK BCL2 MT-ND4 ERBB4 PLG ALK BCL9 SPTA1 EP300 KIT AMER1 PIK3CB MC4R TNRC6B CDK2 ESR1 MAPK11 THRB PSMA3 RPS27 TOP2B ARID1A ERBB2 MAPK14 BCR RPL13 FRK MAP3K21 AKT1 MTOR SMG1 TOP1 NTRK1 PTGIR PPARD CHEK1 MAP3K1 HDAC9 TOP2A INSR GLP1R ACVR2A ATM MMP1 CYP17A1 VDR RET SYK PPARA SRC CTNNB1 CYP11A1 CDK4 PDGFRA MAP3K11 ITK CTNND1 TCF7L2 IL6 RARG KDR GCGR SMAD1 PRKCA RAF1 RPLP0 EEF2 FLT3 ZFP36L2 OLIG2 CSNK1A1 NR3C1 RARB ADRB3 TGFBR1 ROCK1 HDAC1 CSNK1E HLA-A HDAC4 MGAM EPHA2 MTNR1B CHD4 PRKCE JAK2 PRKD1 NCF1 WEE1 HTR6 PABPC1 ABL1 TYMS ESR2 IL1R1 AVPR2 IDH1 PCBP1 EGFR FYN LCK PAK1 AXL PEX5 EZH2 TP53 YES1 PGR VEGFA ADORA1 BLK DDB1 JUN CYP19A1 CSF1R EPCAM OXTR SMARCA4 DUSP16 CREBBP IKBKB GNAS TSHR SSTR2 TUBB SMN1 NRAS XPO1 ADRB2 FLT1 GNRHR LYN SMN2 AR HDAC3 HSP90AA1 ALOX12 PDPK1 RPL14 FAM83B MAP2K2 ZBTB7A IGF1R MAP2K4 PIK3CG IL2 RNF43 MAP2K1 PAK4 ABCB1 RXRA ACVR1 RPS20 RRM2B FNTA PARP1 MME TGIF1 PTK6 UBE2N BCL9L FNTB DNMT1 MET DRD1 FGFR2 RPS6 MGA PRKCQ PPARG SMAD2 TBXA2R FGFR3 RPS26 ARID1B TGFB1 GSK3B HCK FGFR1 JAK3 RPS27A PSPC1 BRAF CDK9 MMP7 RPS3 CDK6 ADORA2A HDAC2 KRAS SMAD3 PLK1 PDGFRB PIK3CA PRKCZ PTGER4 FBXW7 PIK3CD SMAD4 CSNK2A1 PTEN RPS6KB1 PARP2 PTGER2 SIN3A ERBB3 TNF PRKDC SOX9 JAK1 PTGS2 TNNC1 EPAS1 PIK3R1 RBM10 CDK5 RARA CCND1 ELF3 TUBA1B PNRC2 Extended Data Fig. 9 | Example druggability network for colorectal cancer. Nodes acting as cancer-specific drivers are shaded purple. Edge visual properties are as follows: OncoKB interactions, red contiguous arrow; Signor interactions, green contiguous arrow; Signor inhibitors, black vertical slash; complex, black zigzag; direct interaction, red solid line; direct X-ray interaction, green solid line; direct non-protein data bank interaction, blue solid line; reaction, blue contiguous arrow; transcriptional interaction, black sinewave. Figure generated using Cytoscape 69 .
+
RUNX1 IFNG PRKCD ASXL1 APC HNF4A PRKCI HDAC6 CDK1 HLA-B BTK BCL2 MT-ND4 ERBB4 PLG ALK BCL9 SPTA1 EP300 KIT AMER1 PIK3CB MC4R TNRC6B CDK2 ESR1 MAPK11 THRB PSMA3 RPS27 TOP2B ARID1A ERBB2 MAPK14 BCR RPL13 FRK MAP3K21 AKT1 MTOR SMG1 TOP1 NTRK1 PTGIR PPARD CHEK1 MAP3K1 HDAC9 TOP2A INSR GLP1R ACVR2A ATM MMP1 CYP17A1 VDR RET SYK PPARA SRC CTNNB1 CYP11A1 CDK4 PDGFRA MAP3K11 ITK CTNND1 TCF7L2 IL6 RARG KDR GCGR SMAD1 PRKCA RAF1 RPLP0 EEF2 FLT3 ZFP36L2 OLIG2 CSNK1A1 NR3C1 RARB ADRB3 TGFBR1 ROCK1 HDAC1 CSNK1E HLA-A HDAC4 MGAM EPHA2 MTNR1B CHD4 PRKCE JAK2 PRKD1 NCF1 WEE1 HTR6 PABPC1 ABL1 TYMS ESR2 IL1R1 AVPR2 IDH1 PCBP1 EGFR FYN LCK PAK1 AXL PEX5 EZH2 TP53 YES1 PGR VEGFA ADORA1 BLK DDB1 JUN CYP19A1 CSF1R EPCAM OXTR SMARCA4 DUSP16 CREBBP IKBKB GNAS TSHR SSTR2 TUBB SMN1 NRAS XPO1 ADRB2 FLT1 GNRHR LYN SMN2 AR HDAC3 HSP90AA1 ALOX12 PDPK1 RPL14 FAM83B MAP2K2 ZBTB7A IGF1R MAP2K4 PIK3CG IL2 RNF43 MAP2K1 PAK4 ABCB1 RXRA ACVR1 RPS20 RRM2B FNTA PARP1 MME TGIF1 PTK6 UBE2N BCL9L FNTB DNMT1 MET DRD1 FGFR2 RPS6 MGA PRKCQ PPARG SMAD2 TBXA2R FGFR3 RPS26 ARID1B TGFB1 GSK3B HCK FGFR1 JAK3 RPS27A PSPC1 BRAF CDK9 MMP7 RPS3 CDK6 ADORA2A HDAC2 KRAS SMAD3 PLK1 PDGFRB PIK3CA PRKCZ PTGER4 FBXW7 PIK3CD SMAD4 CSNK2A1 PTEN RPS6KB1 PARP2 PTGER2 SIN3A ERBB3 TNF PRKDC SOX9 JAK1 PTGS2 TNNC1 EPAS1 PIK3R1 RBM10 CDK5 RARA CCND1 ELF3 TUBA1B PNRC2 Extended Data Fig. 9 | Example druggability network for colorectal cancer. Nodes acting as cancer-specific drivers are shaded purple. Edge visual properties are as follows: OncoKB interactions, red contiguous arrow; Signor interactions, green contiguous arrow; Signor inhibitors, black vertical slash; complex, black zigzag; direct interaction, red solid line; direct X-ray interaction, green solid line; direct non-protein data bank interaction, blue solid line; reaction, blue contiguous arrow; transcriptional interaction, black sinewave. Figure generated using Cytoscape 69 .
Nature Genetics