Refactor regression documentation to fix consistency issues (#2524)

docs/regressions/regressions-beir-v1.0.0-arguana.splade-pp-ed.cached.md

@@ -1,14 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — ArguAna
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using pre-encoded queries)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using cached queries)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — ArguAna](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — ArguAna](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 
 > Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. [From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective.](https://dl.acm.org/doi/10.1145/3477495.3531857) _Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval_, pages 2353–2359.
 
-In these experiments, we are using pre-encoded queries (i.e., cached results of query encoding).
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
 
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-arguana.splade-pp-ed.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-arguana.splade-pp-ed.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead and then run `bin/build.sh` to rebuild the documentation.

docs/regressions/regressions-beir-v1.0.0-arguana.splade-pp-ed.onnx.md

@@ -1,8 +1,8 @@
 # Anserini Regressions: BEIR (v1.0.0) — ArguAna
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — ArguAna](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — ArguAna](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 

docs/regressions/regressions-beir-v1.0.0-arguana.unicoil-noexp.cached.md

@@ -1,12 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — ArguAna
 
-**Model**: uniCOIL (without any expansions)
+**Model**: uniCOIL without any expansions (using cached queries)
 
 This page describes regression experiments, integrated into Anserini's regression testing framework, using uniCOIL (without any expansions) on [BEIR (v1.0.0) — ArguAna](http://beir.ai/).
 The uniCOIL model is described in the following paper:
 
 > Jimmy Lin and Xueguang Ma. [A Few Brief Notes on DeepImpact, COIL, and a Conceptual Framework for Information Retrieval Techniques.](https://arxiv.org/abs/2106.14807) _arXiv:2106.14807_.
 
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
+
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-arguana.unicoil-noexp.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-arguana.unicoil-noexp.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.
 

docs/regressions/regressions-beir-v1.0.0-bioasq.splade-pp-ed.cached.md

@@ -1,14 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — BioASQ
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using pre-encoded queries)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using cached queries)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — BioASQ](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — BioASQ](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 
 > Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. [From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective.](https://dl.acm.org/doi/10.1145/3477495.3531857) _Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval_, pages 2353–2359.
 
-In these experiments, we are using pre-encoded queries (i.e., cached results of query encoding).
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
 
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-bioasq.splade-pp-ed.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-bioasq.splade-pp-ed.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead and then run `bin/build.sh` to rebuild the documentation.

docs/regressions/regressions-beir-v1.0.0-bioasq.splade-pp-ed.onnx.md

@@ -1,8 +1,8 @@
 # Anserini Regressions: BEIR (v1.0.0) — BioASQ
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — BioASQ](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — BioASQ](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 

docs/regressions/regressions-beir-v1.0.0-bioasq.unicoil-noexp.cached.md

@@ -1,12 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — BioASQ
 
-**Model**: uniCOIL (without any expansions)
+**Model**: uniCOIL without any expansions (using cached queries)
 
 This page describes regression experiments, integrated into Anserini's regression testing framework, using uniCOIL (without any expansions) on [BEIR (v1.0.0) — BioASQ](http://beir.ai/).
 The uniCOIL model is described in the following paper:
 
 > Jimmy Lin and Xueguang Ma. [A Few Brief Notes on DeepImpact, COIL, and a Conceptual Framework for Information Retrieval Techniques.](https://arxiv.org/abs/2106.14807) _arXiv:2106.14807_.
 
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
+
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-bioasq.unicoil-noexp.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-bioasq.unicoil-noexp.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.
 

docs/regressions/regressions-beir-v1.0.0-climate-fever.splade-pp-ed.cached.md

@@ -1,14 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — Climate-FEVER
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using pre-encoded queries)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using cached queries)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — Climate-FEVER](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — Climate-FEVER](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 
 > Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. [From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective.](https://dl.acm.org/doi/10.1145/3477495.3531857) _Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval_, pages 2353–2359.
 
-In these experiments, we are using pre-encoded queries (i.e., cached results of query encoding).
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
 
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-climate-fever.splade-pp-ed.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-climate-fever.splade-pp-ed.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead and then run `bin/build.sh` to rebuild the documentation.

docs/regressions/regressions-beir-v1.0.0-climate-fever.splade-pp-ed.onnx.md

@@ -1,8 +1,8 @@
 # Anserini Regressions: BEIR (v1.0.0) — Climate-FEVER
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — Climate-FEVER](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — Climate-FEVER](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 

docs/regressions/regressions-beir-v1.0.0-climate-fever.unicoil-noexp.cached.md

@@ -1,12 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — Climate-FEVER
 
-**Model**: uniCOIL (without any expansions)
+**Model**: uniCOIL without any expansions (using cached queries)
 
 This page describes regression experiments, integrated into Anserini's regression testing framework, using uniCOIL (without any expansions) on [BEIR (v1.0.0) — Climate-FEVER](http://beir.ai/).
 The uniCOIL model is described in the following paper:
 
 > Jimmy Lin and Xueguang Ma. [A Few Brief Notes on DeepImpact, COIL, and a Conceptual Framework for Information Retrieval Techniques.](https://arxiv.org/abs/2106.14807) _arXiv:2106.14807_.
 
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
+
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-climate-fever.unicoil-noexp.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-climate-fever.unicoil-noexp.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.
 

docs/regressions/regressions-beir-v1.0.0-cqadupstack-android.splade-pp-ed.cached.md

@@ -1,14 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — CQADupStack-android
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using pre-encoded queries)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using cached queries)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-android](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-android](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 
 > Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. [From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective.](https://dl.acm.org/doi/10.1145/3477495.3531857) _Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval_, pages 2353–2359.
 
-In these experiments, we are using pre-encoded queries (i.e., cached results of query encoding).
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
 
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-cqadupstack-android.splade-pp-ed.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-cqadupstack-android.splade-pp-ed.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead and then run `bin/build.sh` to rebuild the documentation.

docs/regressions/regressions-beir-v1.0.0-cqadupstack-android.splade-pp-ed.onnx.md

@@ -1,8 +1,8 @@
 # Anserini Regressions: BEIR (v1.0.0) — CQADupStack-android
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-android](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-android](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 

docs/regressions/regressions-beir-v1.0.0-cqadupstack-android.unicoil-noexp.cached.md

@@ -1,12 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — CQADupStack-android
 
-**Model**: uniCOIL (without any expansions)
+**Model**: uniCOIL without any expansions (using cached queries)
 
 This page describes regression experiments, integrated into Anserini's regression testing framework, using uniCOIL (without any expansions) on [BEIR (v1.0.0) — CQADupStack-android](http://beir.ai/).
 The uniCOIL model is described in the following paper:
 
 > Jimmy Lin and Xueguang Ma. [A Few Brief Notes on DeepImpact, COIL, and a Conceptual Framework for Information Retrieval Techniques.](https://arxiv.org/abs/2106.14807) _arXiv:2106.14807_.
 
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
+
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-cqadupstack-android.unicoil-noexp.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-cqadupstack-android.unicoil-noexp.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead.
 

docs/regressions/regressions-beir-v1.0.0-cqadupstack-english.splade-pp-ed.cached.md

@@ -1,14 +1,14 @@
 # Anserini Regressions: BEIR (v1.0.0) — CQADupStack-english
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using pre-encoded queries)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using cached queries)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-english](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-english](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details:
 
 > Thibault Formal, Carlos Lassance, Benjamin Piwowarski, and Stéphane Clinchant. [From Distillation to Hard Negative Sampling: Making Sparse Neural IR Models More Effective.](https://dl.acm.org/doi/10.1145/3477495.3531857) _Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval_, pages 2353–2359.
 
-In these experiments, we are using pre-encoded queries (i.e., cached results of query encoding).
+In these experiments, we are using cached queries (i.e., cached results of query encoding).
 
 The exact configurations for these regressions are stored in [this YAML file](../../src/main/resources/regression/beir-v1.0.0-cqadupstack-english.splade-pp-ed.cached.yaml).
 Note that this page is automatically generated from [this template](../../src/main/resources/docgen/templates/beir-v1.0.0-cqadupstack-english.splade-pp-ed.cached.template) as part of Anserini's regression pipeline, so do not modify this page directly; modify the template instead and then run `bin/build.sh` to rebuild the documentation.

docs/regressions/regressions-beir-v1.0.0-cqadupstack-english.splade-pp-ed.onnx.md

@@ -1,8 +1,8 @@
 # Anserini Regressions: BEIR (v1.0.0) — CQADupStack-english
 
-**Model**: [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
+**Model**: [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) (using ONNX for on-the-fly query encoding)
 
-This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ (CoCondenser-EnsembleDistil)](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-english](http://beir.ai/).
+This page describes regression experiments, integrated into Anserini's regression testing framework, using [SPLADE++ CoCondenser-EnsembleDistil](https://arxiv.org/abs/2205.04733) on [BEIR (v1.0.0) — CQADupStack-english](http://beir.ai/).
 The model itself can be download [here](https://huggingface.co/naver/splade-cocondenser-ensembledistil).
 See the [official SPLADE repo](https://github.com/naver/splade) and the following paper for more details: