NMT_Papers (Update Continuously)

Some Papers about NMT (Neural Machine Translation)

Some papers I have read about NMT.

Machine translation is a very interesting research direction! Hope you can fine something you need(like)!

If you are interested in machine translation and have any questions, please feel free to contact me!

• Must Reads
• Analysis
• Attention Mechanism
• Model Improvement
• Discourse and Document-level NMT
• Leanring Framework and Objective Function
• Robustness
• Data Augmentation
• Low Source
• Domain adaptation
• Multi-lingual NMT
• Incorporate External Knowledge
• Open Vocabulary Problem
• Evaluation
• Unsupervised NMT

Must Reads

• Sequence to Sequence Learning with Neural Networks. Ilya Sutskever, Oriol Vinyals, Quoc V. Le. NIPS 2014. paper

• Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation. Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, Yoshua Bengio. EMNLP 2014. paper

• Neural Machine Translation by Jointly Learning to Align and Translate. Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio. ICLR 2015. paper

• Effective Approaches to Attention-based Neural Machine Translation. Minh-Thang Luong, Hieu Pham, Christopher D. Manning. EMNLP 2015. paper

• Convolutional Sequence to Sequence Learning. Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin. ICML 2017. paper

• Attention Is All You Need. Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, Illia Polosukhin. NIPS 2017. paper

• BLEU: a Method for Automatic Evaluation of Machine Translation. Kishore Papineni, Salim Roukos, Todd Ward, Wei-Jing Zhu. ACL 2002. paper

• Neural Machine Translation of Rare Words with Subword Units. Rico Sennrich and Barry Haddow and Alexandra Birch. ACL 2016. paper code

Analysis:

• Does String-Based Neural MT Learn Source Syntax?. Xing Shi, Inkit Padhi, and Kevin Knight. EMNLP 2016. paper

• What do Neural Machine Translation Models Learn about Morphology? Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, Hassan Sajjad, James Glass. ACL 2017. paper code

• The Lazy Encoder: A Fine-Grained Analysis of the Role of Morphology in Neural Machine Translation. Arianna Bisazza, Clara Tump. EMNLP 2018. paper

• Evaluating Layers of Representation in Neural Machine Translation on Part-of-Speech and Semantic Tagging Tasks. Yonatan Belinkov, Lluís Màrquez, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James Glass. ICJNLP 2017. paper

• On the Evaluation of Semantic Phenomena in Neural Machine Translation Using Natural Language Inference Adam Poliak, Yonatan Belinkov, James Glass, Benjamin Van Durme. NAACL 2018. paper code

• Beyond Error Propagation in Neural Machine Translation: Characteristics of Language Also Matter. Lijun Wu, Xu Tan, Di He, Fei Tian, Tao Qin, Jianhuang Lai, Tie-Yan Liu. EMNLP 2018. paper

• When and Why are Pre-trained Word Embeddings Useful for Neural Machine Translation? Ye Qi, Devendra Singh Sachan, Matthieu Felix, Sarguna Janani Padmanabhan, Graham Neubig. NAACL 2018. paper code

• A Comparison of Transformer and Recurrent Neural Networks on Multilingual Neural Machine Translation. Surafel M. Lakew, Mauro Cettolo, Marcello Federico. COLING 2018. paper

• Context and Copying in Neural Machine Translation. Rebecca Knowles, Philipp Koehn. EMNLP 2018. paper

• Getting Gender Right in Neural Machine Translation. Eva Vanmassenhove, Christian Hardmeier, Andy Way. EMNLP 2018. paper

• On the Impact of Various Types of Noise on Neural Machine Translation. Huda Khayrallah, Philipp Koehn. WNGT 2018. paper

• Visualizing and Understanding Neural Machine Translation. Yanzhuo Ding, Yang Liu, Huanbo Luan, Maosong Sun. ACL 2017. paper

• Massive Exploration of Neural Machine Translation Architectures. Denny Britz, Anna Goldie, Minh-Thang Luong, Quoc Le. ACL 2017. paper

• One Size Does Not Fit All: Comparing NMT Representations of Different Granularities. Nadir Durrani, Fahim Dalvi, Hassan Sajjad, Yonatan Belinkov, Preslav Nakov. NAACL 2019. paper

• A Call for Prudent Choice of Subword Merge Operations in Neural Machine Translation. Shuoyang Ding, Adithya Renduchintala, Kevin Duh. MT Summit 2019. paper

• Probing the Need for Visual Context in Multimodal Machine Translation. Ozan Caglayan, Pranava Madhyastha, Lucia Specia, Loïc Barrault. NAACL 2019. paper

• Towards Understanding Neural Machine Translation with Word Importance. Shilin He, Zhaopeng Tu, Xing Wang, Longyue Wang, Michael R. Lyu, Shuming Shi. EMNLP 2019. paper

• The Bottom-up Evolution of Representations in the Transformer: A Study with Machine Translation and Language Modeling Objectives. Elena Voita, Rico Sennrich, Ivan Titov. EMNLP 2019. paper

• Understanding Data Augmentation in Neural Machine Translation: Two Perspectives towards Generalization. Guanlin Li, Lemao Liu, Guoping Huang, Conghui Zhu, Tiejun Zhao. EMNLP 2019. paper

Attention Analysis

• An Analysis of Encoder Representations in Transformer-Based Machine Translation. Alessandro Raganato and Jorg Tiedemann. EMNLP Worshopp BlackboxNLP 2018. paper

• How Much Attention Do You Need? A Granular Analysis of Neural Machine Translation Architectures. Tobias Domhan. ACL 2018. paper

• Why Self-Attention? A Targeted Evaluation of Neural Machine Translation Architectures. Gongbo Tang, Mathias Müller, Annette Rios, Rico Sennrich. EMNLP 2018. paper

• An Analysis of Attention Mechanisms: The Case of Word Sense Disambiguation in Neural Machine Translation. Gongbo Tang, Rico Sennrich, Joakim Nivre. WMT 2018. paper

• Encoders Help You Disambiguate Word Senses in Neural Machine Translation. Gongbo Tang, Rico Sennrich, Joakim Nivre. EMNLP 2019. paper

• Assessing the Ability of Self-Attention Networks to Learn Word Order. Baosong Yang, Longyue Wang, Derek F. Wong, Lidia S. Chao, Zhaopeng Tu. ACL 2019. paper code

• Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned. Elena Voita, David Talbot, Fedor Moiseev, Rico Sennrich, Ivan Titov. ACL 2019. paper code

• Are Sixteen Heads Really Better than One?. Paul Michel, Omer Levy, Graham Neubig. NIPS 2019. paper code

Attention Mechanism:

RNN seq2seq:

• Interactive Attention for Neural Machine Translation. Fandong Meng, Zhengdong Lu, Hang Li, Qun Liu. COLING 2016. paper

• An Empirical Study of Adequate Vision Span for Attention-Based Neural Machine Translation. Raphael Shu, Hideki Nakayama. WNGT 2017. paper

• Neural Machine Translation with Recurrent Attention Modeling. Zichao Yang, Zhiting Hu, Yuntian Deng, Chris Dyer, Alex Smola. EACL 2017. paper

• Neural Machine Translation with Deep Attention. Biao Zhang, Deyi Xiong, Jinsong Su. IEEE 2018. paper

• Learning When to Concentrate or Divert Attention: Self-Adaptive Attention Temperature for Neural Machine Translation. Junyang Lin, Xu Sun, Xuancheng Ren, Muyu Li, Qi Su. EMNLP 2018. paper

• Surprisingly Easy Hard-Attention for Sequence to Sequence Learning. Shiv Shankar, Siddhant Garg, Sunita Sarawagi. EMNLP 2018. paper

• Sparse and Constrained Attention for Neural Machine Translation. Chaitanya Malaviya, Pedro Ferreira, André F. T. Martins. ACL 2018. paper

• Attention Focusing for Neural Machine Translation by Bridging Source and Target Embeddings. Shaohui Kuang, Junhui Li, António Branco, Weihua Luo, Deyi Xiong. ACL 2018. paper

• Word Attention for Sequence to Sequence Text Understanding. Lijun Wu, Fei Tian, Li Zhao, Jianhuang Lai, Tie-Yan Liu. AAAI 2018. paper

• Attention-via-Attention Neural Machine Translation. Shenjian Zhao, Zhihua Zhang. AAAI 2018. paper

• Combining Character and Word Information in Neural Machine Translation Using a Multi-Level Attention. Huadong Chen, Shujian Huang, David Chiang, Xinyu Dai, Jiajun Chen. NAACL 2018. paper

• Target Foresight based Attention for Neural Machine Translation. Xintong Li, Lemao Liu, Zhaopeng Tu, Shuming Shi, Max Meng. NAACL 2018. paper

• Neural Machine Translation with Decoding-History Enhanced Attention. Mingxuan Wang, Jun Xie, Zhixing Tan, Jinsong Su, Deyi Xiong, Chao bian. COLING 2018. paper

Transformer:

• Accelerating Neural Transformer via an Average Attention Network. Biao Zhang, Deyi Xiong, Jinsong Su. ACL 2018. paper code

• Self-Attention with Relative Position Representations. Peter Shaw, Jakob Uszkoreit, Ashish Vaswani. ACL 2018. paper

• Modeling Localness for Self-Attention Networks. Baosong Yang, Zhaopeng Tu, Derek F. Wong, Fandong Meng, Lidia S. Chao, Tong Zhang. EMNLP 2018. paper

• On The Alignment Problem In Multi-Head Attention-Based Neural Machine Translation. Tamer Alkhouli, Gabriel Bretschner, Hermann Ney. WMT 2018. paper

• Multi-Head Attention with Disagreement Regularization. Jian Li, Zhaopeng Tu, Baosong Yang, Michael R. Lyu, Tong Zhang. EMNLP 2018. paper

• Information Aggregation for Multi-Head Attention with Routing-by-Agreement. Jian Li, Baosong Yang, Zi-Yi Dou, Xing Wang, Michael R. Lyu, Zhaopeng Tu. NAACL 2019. paper

• Pay Less Attention with Lightweight and Dynamic Convolutions. Felix Wu, Angela Fan, Alexei Baevski, Yann N. Dauphin, Michael Auli. ICLR 2019. paper

• Convolutional Self-Attention Network. Baosong Yang, Longyue Wang, Derek F. Wong, Lidia S. Chao, Zhaopeng Tu. NAACL 2019. paper

• Context-Aware Self-Attention Networks. Baosong Yang, Jian Li, Derek Wong, Lidia S. Chao, Xing Wang, Zhaopeng Tu. AAAI 2019. paper

• Leveraging Local and Global Patterns for Self-Attention Networks. Mingzhou Xu, Derek F. Wong, Baosong Yang, Yue Zhang, Lidia S. Chao. ACL 2019. paper code

• Widening the Representation Bottleneck in Neural Machine Translation with Lexical Shortcuts. Denis Emelin, Ivan Titov, Rico Sennrich. WMT 2019. paper code

• Self-Attention Networks with Structural Position Encoding. Xing Wang, Zhaopeng Tu, Longyue Wang, and Shuming Shi. EMNLP 2019. paper

• Multi-Granularity Self-Attention for Neural Machine Translation. Jie Hao, Xing Wang, Shuming Shi, Jinfeng Zhang, and Zhaopeng Tu. EMNLP 2019. paper

• Towards Better Modeling Hierarchical Structure for Self-Attention with Ordered Neurons. Jie Hao, Xing Wang, Shuming Shi, Jinfeng Zhang, Zhaopeng Tu. EMNLP 2019. paper

• Mixed Multi-Head Self-Attention for Neural Machine Translation. Hongyi Cui, Shohei Iida, Po-Hsuan Hung, Takehito Utsuro, Masaaki Nagata. WNGT 2019. paper

Model Improvement:

RNN seq2seq:

• Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, Jeffrey Dean. 2016. paper

• You May Not Need Attention. Ofir Press, Noah A. Smith. 2018. paper

• Context Gates for Neural Machine Translation. Zhaopeng Tu, Yang Liu, Zhengdong Lu, Xiaohua Liu, Hang Li. TACL 2017. paper

• A Context-Aware Recurrent Encoder for Neural Machine Translation. Biao Zhang, Deyi Xiong, Jinsong Su, Hong Duan. IEEE/ACM Transactions on Audio, Speech, and Language Processing 2017. paper

• Context-Dependent Word Representation for Neural Machine Translation. Heeyoul Choi, Kyunghyun Cho, Yoshua Bengio. paper

• Handling Homographs in Neural Machine Translation. Frederick Liu, Han Lu, Graham Neubig. NAACL 2018. paper code

• Improving Neural Machine Translation by Incorporating Hierarchical Subword Features. Makoto Morishita, Jun Suzuki and Masaaki Nagata. COLING 2018. paper

• Compositional Representation of Morphologically-Rich Input for Neural Machine Translation. Duygu Ataman, Marcello Federico. ACL 2018. paper

• Refining Source Representations with Relation Networks for Neural Machine Translation. Wen Zhang, Jiawei Hu, Yang Feng, Qun Liu. NAACL 2018. paper

• Improving Lexical Choice in Neural Machine Translation. Toan Q. Nguyen, David Chiang. ACL 2018. paper code

• Memory-enhanced Decoder for Neural Machine Translation. Mingxuan Wang, Zhengdong Lu, Hang Li, Qun Liu. EMNLP 2016. paper

• Memory-augmented Neural Machine Translation. Yang Feng, Shiyue Zhang, Andi Zhang, Dong Wang, Andrew Abel. EMNLP 2017. paper

• Neural Machine Translation with Recurrent Attention Modeling. Zichao Yang, Zhiting Hu, Yuntian Deng, Chris Dyer, Alex Smola. EACL 2017. paper

• Learning to Remember Translation History with a Continuous Cache. haopeng Tu, Yang Liu, Shuming Shi, Tong Zhang. TACL 2018. paper

• Neural Machine Translation with Key-Value Memory-Augmented Attention. Fandong Meng, Zhaopeng Tu, Yong Cheng, Haiyang Wu, Junjie Zhai, Yuekui Yang, Di Wang. IJCAI 2018. paper

• Encoding Gated Translation Memory into Neural Machine Translation. Qian Cao and Deyi Xiong. EMNLP 2018. paper

• Dense Information Flow for Neural Machine Translation. Yanyao Shen, Xu Tan, Di He, Tao Qin, Tie-Yan Liu. COLING 2018. paper

• Adaptive Weighting for Neural Machine Translation. Yachao Li, Junhui Li, Min Zhang. COLING 2018. paper

• Multi-channel Encoder for Neural Machine Translation. Hao Xiong, Zhongjun He, Xiaoguang Hu, Hua Wu. AAAI 2018. paper

• Towards Two-Dimensional Sequence to Sequence Model in Neural Machine Translation. Parnia Bahar, Christopher Brix, Hermann Ney. EMNLP 2018. paper

• Modeling Past and Future for Neural Machine Translation. Zaixiang Zheng, Hao Zhou, Shujian Huang, Lili Mou, Xinyu Dai, Jiajun Chen, Zhaopeng Tu. TACL 2018. paper

• Self-Attentive Residual Decoder for Neural Machine Translation. Lesly Miculicich Werlen, Nikolaos Pappas, Dhananjay Ram, Andrei Popescu-Belis. NAACL 2018. paper code

• Modeling Coverage for Neural Machine Translation. Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, Hang Li. ACL 2016. paper

• A Simple and Effective Approach to Coverage-Aware Neural Machine Translation. Yanyang Li, Tong Xiao, Yinqiao Li, Qiang Wang, Changming Xu, Jingbo Zhu. ACL 2018. paper

• Chunk-Based Bi-Scale Decoder for Neural Machine Translation. Hao Zhou, Zhaopeng Tu, Shujian Huang, Xiaohua Liu, Hang Li, Jiajun Chen. ACL 2017. paper

• Chunk-based Decoder for Neural Machine Translation. Shonosuke Ishiwatari, Jingtao Yao, Shujie Liu, Mu Li, Ming Zhou, Naoki Yoshinaga, Masaru Kitsuregawa, Weijia Jia. ACL 2017. paper

• Deconvolution-Based Global Decoding for Neural Machine Translation. Junyang Lin, Xu Sun, Xuancheng Ren, Shuming Ma, Jinsong Su, Qi Su. COLING 2018. paper

• Asynchronous Bidirectional Decoding for Neural Machine Translation. Xiangwen Zhang, Jinsong Su, Yue Qin, Yang Liu, Rongrong Ji, Hongji Wang. AAAI 2018. paper

• Deliberation Networks: Sequence Generation Beyond One-Pass Decoding. Yingce Xia, Fei Tian, Lijun Wu, Jianxin Lin, Tao Qin, Nenghai Yu, Tie-Yan Liu. NIPS 2017. paper

• Towards Neural Phrase-based Machine Translation. Po-Sen Huang, Chong Wang, Sitao Huang, Dengyong Zhou, Li Deng. ICLR 2018. paper code

• Identifying and Controlling Important Neurons in Neural Machine Translation. Anthony Bau, Yonatan Belinkov, Hassan Sajjad, Nadir Durrani, Fahim Dalvi, James Glass. ICLR 2019. paper

• Towards Linear Time Neural Machine Translation with Capsule Networks. Mingxuan Wang, Jun Xie, Zhixing Tan, Jinsong Su, Deyi xiong, Lei Li. EMNLP 2019. paper

Deeper

• Deep Recurrent Models with Fast-Forward Connections for Neural Machine Translation. Jie Zhou, Ying Cao, Xuguang Wang, Peng Li, Wei Xu. TACL 2016. paper

• Deep Architectures for Neural Machine Translation. Antonio Valerio Miceli Barone, Jindřich Helcl, Rico Sennrich, Barry Haddow, Alexandra Birch. WMT 2017. paper

• Deep Neural Machine Translation with Linear Associative Unit. Mingxuan Wang, Zhengdong Lu, Jie Zhou, Qun Liu. ACL 2017. paper

• DTMT: A Novel Deep Transition Architecture for Neural Machine Translation. Fandong Meng, Jinchao Zhang. AAAI 2019. paper code

Efficiency:

• Compressing Word Embeddings via Deep Compositional Code Learning. Raphael Shu, Hideki Nakayama. ICLR 2018. paper

• Simplifying Neural Machine Translation with Addition-Subtraction Twin-Gated Recurrent Networks. Biao Zhang, Deyi Xiong, Jinsong Su, Qian Lin, Huiji Zhang. EMNLP 2018. paper code

• A Lightweight Recurrent Network for Sequence Modeling. Biao Zhang, Rico Sennrichg. ACL 2019. paper code

Transformer:

• Universal Transformers. Mostafa Dehghani, Stephan Gouws, Oriol Vinyals, Jakob Uszkoreit, Łukasz Kaiser. ICLR 2019. paper

• Weighted Transformer Network for Machine Translation. Karim Ahmed, Nitish Shirish Keskar, Richard Socher. Arxiv 2019. paper

• Layer-Wise Coordination between Encoder and Decoder for Neural Machine Translation. He Tianyu, Tan Xu, Xia Yingce, He Di, Qin Tao, Chen Zhibo, Liu Tie-Yan. NIPS 2018. paper

• Tied Transformers: Neural Machine Translation with Shared Encoder and Decoder. Yingce Xia, Tianyu He, Xu Tan, Fei Tian, Di He and Tao Qin. AAAI 2019. paper

• The Best of Both Worlds: Combining Recent Advances in Neural Machine Translation. Mia Xu Chen, Orhan Firat, Ankur Bapna, Melvin Johnson, Wolfgang Macherey, George Foster, Llion Jones, Niki Parmar, Mike Schuster, Zhifeng Chen, Yonghui Wu, Macduff Hughes. ACL 2018. paper

• Modeling Recurrence for Transformer. Jie Hao, Xing Wang, Baosong Yang, Longyue Wang, Jinfeng Zhang, Zhaopeng Tu. NAACL 2019. paper

• Exploiting Sentential Context for Neural Machine Translation. Xing Wang, Zhaopeng Tu, Longyue Wang, Shuming Shi. ACL 2019. paper

• Multi-layer Representation Fusion for Neural Machine Translation. Qiang Wang, Fuxue Li, Tong Xiao, Yanyang Li, Yinqiao Li, Jingbo Zhu. COLING 2018. paper

• Exploiting Deep Representations for Neural Machine Translation. Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Shuming Shi, Tong Zhang. EMNLP 2018. paper

• Dynamic Layer Aggregation for Neural Machine Translation with Routing-by-Agreement. Zi-Yi Dou, Zhaopeng Tu, Xing Wang, Shuming Shi, Tong Zhang. AAAI 2019. paper

• Dynamic Past and Future for Neural Machine Translation. Zaixiang Zheng, Shujian Huang, Zhaopeng Tu, Xin-Yu Dai, Jiajun Chen. EMNLP 2019. paper

• Neural Machine Translation with Reordering Embeddings. Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita. ACL 2019. paper

• Recurrent Positional Embedding for Neural Machine Translation. Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita. EMNLP 2019. paper

• Transformers without Tears: Improving the Normalization of Self-Attention. Toan Q. Nguyen, Julian Salazar. IWSLT 2019. paper code

• Neuron Interaction Based Representation Composition for Neural Machine Translation. Jian Li, Xing Wang, Baosong Yang, Shuming Shi, Michael R. Lyu, Zhaopeng Tu. AAAI 2020. paper

• Sequence Modeling with Unconstrained Generation Order. Dmitrii Emelianenko, Elena Voita, Pavel Serdyukov. NIPS 2019. paper code

• Neural Machine Translation with Soft Prototype. Yiren Wang, Lijun Wu, Yingce Xia, Tao Qin, ChengXiang Zhai, Tie-Yan Liu. NIPS 2019. paper

Deeper:

• Training Deeper Neural Machine Translation Models with Transparent Attention. Ankur Bapna, Mia Xu Chen, Orhan Firat, Yuan Cao, Yonghui Wu. EMNLP 2018. paper

• Learning Deep Transformer Models for Machine Translation. Qiang Wang, Bei Li, Tong Xiao, Jingbo Zhu, Changliang Li, Derek F. Wong, Lidia S. Chao. ACL 2019. paper code

• Depth Growing for Neural Machine Translation. Lijun Wu, Yiren Wang, Yingce Xia, Fei Tian, Fei Gao, Tao Qin, Jianhuang Lai, Tie-Yan Liu. ACL 2019. paper code

• Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention. Biao Zhang, Ivan Titov, Rico Sennrich. EMNLP 2019. paper code

Efficiency:

• Recurrent Stacking of Layers for Compact Neural Machine Translation Models. Raj Dabre, Atsushi Fujita. AAAI 2019. paper

• Sharing Attention Weights for Fast Transformer. Tong Xiao, Yinqiao Li, Jingbo Zhu, Zhengtao Yu, Tongran Liu. IJCAI 2019. paper

• Shared-Private Bilingual Word Embeddings for Neural Machine Translation. Xuebo Liu, Derek F. Wong, Yang Liu, Lidia S. Chao, Tong Xiao, Jingbo Zhu. ACL 2019. paper

• A Tensorized Transformer for Language Modeling. Xindian Ma, Peng Zhang, Shuai Zhang, Nan Duan, Yuexian Hou, Dawei Song, Ming Zhou. NIPS 2019. paper

• Root Mean Square Layer Normalization. Biao Zhang; Rico Sennrich. NIPS 2019. paper code

Non/Semi Autoregressive NMT:

• Understanding Knowledge Distillation in Non-autoregressive Machine Translation. Chunting Zhou, Graham Neubig, Jiatao Gu. ICLR 2020. paper

• Non-Autoregressive Neural Machine Translation. Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K. Li, Richard Socher. ICLR 2018. paper

• Deterministic Non-Autoregressive Neural Sequence Modeling by Iterative Refinement. Jason Lee, Elman Mansimov, Kyunghyun Cho. EMNLP 2018. paper code

• Latent-Variable Non-Autoregressive Neural Machine Translation with Deterministic Inference Using a Delta Posterior. Raphael Shu, Jason Lee, Hideki Nakayama, Kyunghyun Cho. AAAI 2020. paper code

• Semi-Autoregressive Neural Machine Translation. Chunqi Wang, Ji Zhang, Haiqing Chen. EMNLP 2018. paper

• End-to-End Non-Autoregressive Neural Machine Translation with Connectionist Temporal Classification. Jindřich Libovický, Jindřich Helcl. EMNLP 2018. paper

• Insertion Transformer: Flexible Sequence Generation via Insertion Operations. Mitchell Stern, William Chan, Jamie Kiros, Jakob Uszkoreit. ICML 2019. paper

• Mask-Predict: Parallel Decoding of Conditional Masked Language Models. Marjan Ghazvininejad, Omer Levy, Yinhan Liu, Luke Zettlemoyer. EMNLP 2019. paper code

• Levenshtein Transformer. Jiatao Gu, Changhan Wang, Jake Zhao. NIPS 2019. paper

• Retrieving Sequential Information for Non-Autoregressive Neural Machine Translation. Chenze Shao, Yang Feng, Jinchao Zhang, Fandong Meng, Xilin Chen, Jie Zhou. ACL 2019. paper

• Imitation Learning for Non-Autoregressive Neural Machine Translation. Bingzhen Wei, Mingxuan Wang, Hao Zhou, Junyang Lin, Xu Sun. ACL 2019. paper

• Hint-Based Training for Non-Autoregressive Machine Translation. Zhuohan Li, Zi Lin, Di He, Fei Tian, Tao QIN, Liwei WANG, Tie-Yan Liu. EMNLP 2019. paper

• Non-Autoregressive Neural Machine Translation with Enhanced Decoder Input. Junliang Guo, Xu Tan, Di He, Tao Qin, Linli Xu, Tie-Yan Liu. AAAI 2019. paper

• Non-Autoregressive Machine Translation with Auxiliary Regularization. Yiren Wang, Fei Tian, Di He, Tao Qin, ChengXiang Zhai, Tie-Yan Liu. AAAI 2019. paper

• Syntactically Supervised Transformers for Faster Neural Machine Translation. Nader Akoury, Kalpesh Krishna, Mohit Iyyer. ACL 2019. paper

• Fast Structured Decoding for Sequence Models. Zhiqing Sun, Zhuohan Li, Haoqing Wang, Zi Lin, Di He, Zhi-Hong Deng. NIPS 2019. paper code

• FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow. Xuezhe Ma, Chunting Zhou, Xian Li, Graham Neubig, Eduard Hovy. EMNLP 2019. paper code

• Fine-Tuning by Curriculum Learning for Non-Autoregressive Neural Machine Translation. Junliang Guo, Xu Tan, Linli Xu, Tao Qin, Enhong Chen, Tie-Yan Liu. AAAI 2020. paper

• Minimizing the Bag-of-Ngrams Difference for Non-Autoregressive Neural Machine Translation. Chenze Shao, Jinchao Zhang, Yang Feng, Fandong Meng, Jie Zhou. AAAI 2020. paper code

Weight Tying:

• Using the Output Embedding to Improve Language Models. Ofir Press, Lior Wolf. EACL 2017. paper

• Beyond Weight Tying: Learning Joint Input-Output Embeddings for Neural Machine Translation. Nikolaos Pappas, Lesly Miculicich Werlen, James Henderson. WMT 2018. paper

Convolutional NMT:

• Convolutional Sequence to Sequence Learning. Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin. ICML 2017. paper

• Pervasive Attention: 2D Convolutional Neural Networks for Sequence-to-Sequence Prediction. Maha Elbayad, Laurent Besacier, Jakob Verbeek. CoNLL 2018. paper code

Character Level NMT:

• Fully Character-Level Neural Machine Translation without Explicit Segmentation. Jason Lee, Kyunghyun Cho, Thomas Hofmann. TACL 2017. paper

• Revisiting Character-Based Neural Machine Translation with Capacity and Compression. Colin Cherry, George Foster, Ankur Bapna, Orhan Firat, Wolfgang Macherey. EMNLP 2018. paper

Discourse and Document-level NMT:

• Neural Machine Translation with Extended Context. Jorg Tiedemann and Yves Scherrer. DiscoMT 2017. paper

• Does Neural Machine Translation Benefit from Larger Context?. Sebastien Jean, Stanislas Lauly, Orhan Firat, Kyunghyun Cho. Arxiv 2017. paper

• Exploiting Cross-Sentence Context for Neural Machine Translation. Longyue Wang, Zhaopeng Tu, Andy Way, Qun Liu. EMNLP 2017. paper

• Evaluating Discourse Phenomena in Neural Machine Translation. Rachel Bawden, Rico Sennrich, Alexandra Birch, Barry Haddow. NAACL 2018. paper

• Context-Aware Neural Machine Translation Learns Anaphora Resolution. Elena Voita, Pavel Serdyukov, Rico Sennrich, Ivan Titov. ACL 2018. paper

• When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion. Elena Voita, Rico Sennrich, Ivan Titov. ACL 2019. paper

• Exploiting Cross-Sentence Context for Neural Machine Translation. Longyue Wang, Zhaopeng Tu, Andy Way, Qun Liu. EMNLP 2017. paper

• Document Context Neural Machine Translation with Memory Networks. Sameen Maruf, Gholamreza Haffari. ACL 2018. paper

• Improving the Transformer Translation Model with Document-Level Context. Jiacheng Zhang, Huanbo Luan, Maosong Sun, FeiFei Zhai, Jingfang Xu, Min Zhang, Yang Liu. EMNLP 2018. paper

• Document-Level Neural Machine Translation with Hierarchical Attention Networks. Lesly Miculicich, Dhananjay Ram, Nikolaos Pappas, James Henderson. EMNLP 2018. paper

• Selective Attention for Context-aware Neural Machine Translation. Sameen Maruf, André F. T. Martins, Gholamreza Haffari. NAACL 2019. paper

• Modeling Coherence for Discourse Neural Machine Translation. Hao Xiong, Zhongjun He, Hua Wu, Haifeng Wang. AAAI 2019. paper

• Modeling Coherence for Neural Machine Translation with Dynamic and Topic Caches. Shaohui Kuang, Deyi Xiong, Weihua Luo, Guodong Zhou. COLING 2018. paper

• Fusing Recency into Neural Machine Translation with an Inter-Sentence Gate Model. Shaohui Kuang, Deyi Xiong. COLING 2018. paper

• Hierarchical Modeling of Global Context for Document-Level Neural Machine Translation. Xin Tan, Longyin Zhang, Deyi Xiong, Guodong Zhou. EMNLP 2019. paper

• Enhancing Context Modeling with a Query-Guided Capsule Network for Document-level Translation. Zhengxin Yang, Jinchao Zhang, Fandong Meng, Shuhao Gu, Yang Feng, Jie Zhou. EMNLP 2019. paper

• A Large-Scale Test Set for the Evaluation of Context-Aware Pronoun Translation in Neural Machine Translation. Mathias Müller, Annette Rios, Elena Voita, Rico Sennrichu. WMT 2018. paper

• Coreference and Coherence in Neural Machine Translation: A Study Using Oracle Experiments. Dario Stojanovski, Alexander Fraser. WMT 2018. paper

• Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations. Sameen Maruf, André F. T. Martins, Gholamreza Haffari. WMT 2018. paper

• Context-Aware Learning for Neural Machine Translation. Sébastien Jean, Kyunghyun Cho. WNGT 2019. paper

• Context-Aware Monolingual Repair for Neural Machine Translation. Elena Voita, Rico Sennrich, Ivan Titov. EMNLP 2019. paper code

• When and Why is Document-level Context Useful in Neural Machine Translation? Yunsu Kim, Duc Thanh Tran, Hermann Ney. DiscoMT 2019. paper code

• Fill in the Blanks: Imputing Missing Sentences for Larger-Context Neural Machine Translation Sébastien Jean, Ankur Bapna, Orhan Firat. Arxiv 2019. paper

Dropped Pronoun Problem:

• A Novel Approach to Dropped Pronoun Translation. Longyue Wang, Zhaopeng Tu, Xiaojun Zhang, Hang Li, Andy Way, Qun Liu NAACL 2016. paper

• Translating Pro-Drop Languages with Reconstruction Models. Longyue Wang, Zhaopeng Tu, Shuming Shi, Tong Zhang, Yvette Graham, Qun Liu. AAAI 2018. paper

• Learning to Jointly Translate and Predict Dropped Pronouns with a Shared Reconstruction Mechanism. Longyue Wang, Zhaopeng Tu, Andy Way, Qun Liu. EMNLP 2018. paper

Leanring Framework and Objective Function:

• Dual Learning for Machine Translation. Yingce Xia, Di He, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, Wei-Ying Ma. NIPS 2016. paper

• Sequence-Level Knowledge Distillation. Yoon Kim, Alexander M. Rush. EMNLP 2016. paper

• Minimum Risk Training for Neural Machine Translation. Shiqi Shen, Yong Cheng, Zhongjun He, Wei He, Hua Wu, Maosong Sun, Yang Liu. ACL 2016. paper

• Bag-of-Words as Target for Neural Machine Translation. Shuming Ma, Xu Sun, Yizhong Wang, Junyang Lin. ACL 2018. paper

• Classical Structured Prediction Losses for Sequence to Sequence Learning. Sergey Edunov, Myle Ott, Michael Auli, David Grangier, Marc'Aurelio Ranzato. NAACL 2018. paper

• Beyond BLEU:Training Neural Machine Translation with Semantic Similarity. John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, Graham Neubig. ACL 2019. paper code

• Sentence-wise Smooth Regularization for Sequence to Sequence Learning. Chengyue Gong, Xu Tan, Di He, Tao Qin. AAAI 2019. paper

• Neural Machine Translation with Word Predictions. Rongxiang Weng, Shujian Huang, Zaixiang Zheng, Xinyu Dai, Jiajun Chen. EMNLP 2017. paper

• ReWE: Regressing Word Embeddings for Regularization of Neural Machine Translation Systems. Inigo Jauregi Unanue, Ehsan Zare Borzeshi, Nazanin Esmaili, Massimo Piccardi. NAACL 2019. paper

• Sentence-Level Agreement for Neural Machine Translation. Mingming Yang, Rui Wang, Kehai Chen, Masao Utiyama, Eiichiro Sumita, Min Zhang, Tiejun Zhao. ACL 2019. paper

• Differentiable Sampling with Flexible Reference Word Order for Neural Machine Translation. Weijia Xu, Xing Niu, Marine Carpuat. NAACL 2019. paper code

• Bridging the Gap between Training and Inference for Neural Machine Translation. Wen Zhang, Yang Feng, Fandong Meng, Di You, Qun Liu. ACL 2019. paper

• Reducing Word Omission Errors in Neural Machine Translation: A Contrastive Learning Approach. Zonghan Yang, Yong Cheng, Yang Liu, Maosong Sun. ACL 2019. paper

• Addressing the Under-Translation Problem from the Entropy Perspective. Yang Zhao, Jiajun Zhang, Chengqing Zong, Zhongjun He, Hua Wu. AAAI 2019. paper

• Lost in Machine Translation: A Method to Reduce Meaning Loss. Reuben Cohn-Gordon, Noah Goodman. NAACL 2019. paper

• Self-Supervised Neural Machine Translation. Dana Ruiter, Cristina España-Bonet, Josef van Genabith. ACL 2019. paper

• Multi-agent Learning for Neural Machine Translation. Tianchi Bi, Hao Xiong, Zhongjun He, Hua Wu, Haifeng Wang. EMNLP 2019. paper

• Generative Neural Machine Translation. Harshil Shah, David Barber. NIPS 2018. paper

• Mirror-Generative Neural Machine Translation. Zaixiang Zheng, Hao Zhou, Shujian Huang, Lei Li, Xin-Yu Dai, Jiajun Chen. ICLR 2020. paper

Robustness:

• Robust Neural Machine Translation with Joint Textual and Phonetic Embedding. Hairong Liu, Mingbo Ma, Liang Huang, Hao Xiong, Zhongjun He. ACL 2019. paper

• Robust Neural Machine Translation with Doubly Adversarial Inputs. Yong Cheng, Lu Jiang, Wolfgang Machereye. ACL 2019. paper

• MTNT: A Testbed for Machine Translation of Noisy Text. Paul Michel, Graham Neubig. EMNLP 2018. paper

• Improving Robustness of Machine Translation with Synthetic Noise. Vaibhav Vaibhav, Sumeet Singh, Craig Stewart, Graham Neubig. NAACL 2019. paper

• Synthetic and Natural Noise Both Break Neural Machine Translation. Yonatan Belinkov, Yonatan Bisk. ICLR 2018. paper

• Training on Synthetic Noise Improves Robustness to Natural Noise in Machine Translation. Vladimir Karpukhin, Omer Levy, Jacob Eisenstein, Marjan Ghazvininejad. Arxiv 2019. paper

Data Augmentation:

• Exploiting Source-side Monolingual Data in Neural Machine Translation. Jiajun Zhang, Chengqing Zong. EMNLP 2016. paper

• Dynamic Data Selection for Neural Machine Translation. Marlies van der Wees, Arianna Bisazza, Christof Monzy. EMNLP 2017. paper

• Fixing Translation Divergences in Parallel Corpora for Neural MT. MinhQuang Pham, Josep Crego, Jean Senellart, François Yvon. EMNLP 2018. paper

• SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translation. Xinyi Wang, Hieu Pham, Zihang Dai, Graham Neubig. EMNLP 2018. paper

• Code-Switching for Enhancing NMT with Pre-Specified Translation. Kai Song, Yue Zhang, Heng Yu, Weihua Luo, Kun Wang, Min Zhang. NAACL 2019. paper

• Soft Contextual Data Augmentation for Neural Machine Translation. Jinhua Zhu, Fei Gao, Lijun Wu, Yingce Xia, Tao Qin, Wengang Zhou, Xueqi Cheng, Tie-Yan Liu. ACL 2019. paper code

• Exploiting Monolingual Data at Scale for Neural Machine Translation. Lijun Wu, Yiren Wang, Yingce Xia, Tao QIN, Jianhuang Lai, Tie-Yan Liu. EMNLP 2019. paper

Back-Translation:

• Improving Neural Machine Translation Models with Monolingual Data. Rico Sennrich, Barry Haddow, Alexandra Birch. ACL 2016. paper

• Back-Translation Sampling by Targeting Difficult Words in Neural Machine Translation. Marzieh Fadaee, Christof Monz. EMNLP 2018. paper

• Understanding Back-Translation at Scale. Sergey Edunov, Myle Ott, Michael Auli, David Grangier. EMNLP 2018. paper

• Generalizing Back-Translation in Neural Machine Translation. Miguel Graça, Yunsu Kim, Julian Schamper, Shahram Khadivi, Hermann Ney. WMT 2019. paper

• Iterative Back-Translation for Neural Machine Translation. Vu Cong Duy Hoang, Philipp Koehn, Gholamreza Haffari, Trevor Cohn. WNGT 2018. paper

• Tagged Back-Translation. Isaac Caswell, Ciprian Chelba, David Grangier. WMT 2019. paper

• Improving Back-Translation with Uncertainty-based Confidence Estimation. Shuo Wang, Yang Liu, Chao Wang, Huanbo Luan, Maosong Sun. EMNLP 2019. paper

• APE at Scale and its Implications on MT Evaluation Biases. Markus Freitag, Isaac Caswell, Scott Roy. WMT 2019. paper

Low Source:

• Revisiting Low-Resource Neural Machine Translation: A Case Study. Rico Sennrich, Biao Zhang. ACL 2019. paper

• Copied Monolingual Data Improves Low-Resource Neural Machine Translation. Anna Currey, Antonio Valerio Miceli Barone, and Kenneth Heafield. WMT 2017. paper

• Data Augmentation for Low-Resource Neural Machine Translation. Marzieh Fadaee, Arianna Bisazza, Christof Monz. ACL 2017. paper

• Rapid Adaptation of Neural Machine Translation to New Languages. Graham Neubig, Junjie Hu. EMNLP 2018. paper

• Generalized Data Augmentation for Low-Resource Translation. Mengzhou Xia, Xiang Kong, Antonios Anastasopoulos, Graham Neubigz. ACL 2019. paper code

• Handling Syntactic Divergence in Low-resource Machine Translation. Chunting Zhou, Xuezhe Ma, Junjie Hu, Graham Neubig. EMNLP 2019. paper code

Domain adaptation:

• Sentence Embedding for Neural Machine Translation Domain Adaptation. Rui Wang, Andrew Finch, Masao Utiyama and Eiichiro Sumita. ACL 2017. paper

• Adapting Neural Machine Translation with Parallel Synthetic Data. Mara Chinea-R´ıos, Alvaro Peris, Francisco Casacuberta. WMT 2017. paper

• Multi-Domain Neural Machine Translation with Word-Level Domain Context Discrimination. Jiali Zeng, Jinsong Su, Huating Wen, Yang Liu, Jun Xie, Yongjing Yin, Jianqiang Zhao. EMNLP 2018. paper

• Extreme Adaptation for Personalized Neural Machine Translation. Paul Michel, Graham Neubig. ACL 2018. paper

• Learning Hidden Unit Contribution for Adapting Neural Machine Translation Models. David Vilar. NAACL 2018. paper

• Improving Domain Adaptation Translation with Domain Invariant and Specific Information. Shuhao Gu, Yang Feng, Qun Liu. NAACL 2019. paper

• Unsupervised Domain Adaptation for Neural Machine Translation with Domain-Aware Feature Embeddings. Zi-Yi Dou, Junjie Hu, Antonios Anastasopoulos, Graham Neubig. EMNLP 2019. paper code

• Iterative Dual Domain Adaptation for Neural Machine Translation. Jiali Zeng, Yang Liu, Jinsong Su, Yubin Ge, Yaojie Lu, Yongjing Yin, Jiebo Luo. EMNLP 2019. paper

Multi-lingual NMT:

• Multi-Source Neural Translation. Barret Zoph and Kevin Knight. NAACL 2016. paper

• Multi-task Sequence to Sequence Learning. Minh-Thang Luong, Quoc V. Le, Ilya Sutskever, Oriol Vinyals, Lukasz Kaiser. ICLR 2016. paper

• Contextual Parameter Generation for Universal Neural Machine Translation. Emmanouil Antonios Platanios, Mrinmaya Sachan, Graham Neubig, Tom Mitchell. EMNLP 2018. paper

• Rapid Adaptation of Neural Machine Translation to New Languages. Graham Neubig, Junjie Hu. EMNLP 2018. paper

• Three Strategies to Improve One-to-Many Multilingual Translation. Yining Wang, Jiajun Zhang, Feifei Zhai, Jingfang Xu and Chengqing Zong. EMNLP 2018. paper

• Parameter Sharing Methods for Multilingual Self-Attentional Translation Models. Devendra Singh Sachan, Graham Neubig. WMT 2018. paper

• Addressing word-order Divergence in Multilingual Neural Machine Translation for extremely Low Resource Languages. Rudra Murthy V, Anoop Kunchukuttan, Pushpak Bhattacharyya. ACL 2018. paper

• Multi-Source Neural Machine Translation with Data Augmentation. Yuta Nishimura, Katsuhito Sudoh, Graham Neubig, Satoshi Nakamura. IWSLT 2018. paper

Incorporate External Knowledge:

• Inducing Grammars with and for Neural Machine Translation. Ke Tran, Yonatan Bisk. WNGT 2018. paper

• Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning. Tobias Domhan and Felix Hieber. EMNLP 2017. paper

• Neural System Combination for Machine Translation. Long Zhou, Wenpeng Hu, Jiajun Zhang, Chengqing Zong. ACL 2017. paper

• Modeling Source Syntax for Neural Machine Translation. Junhui Li, Deyi Xiong, Zhaopeng Tu, Muhua Zhu, Min Zhang, Guodong Zhou. ACL 2017. paper

• Syntax-Directed Attention for Neural Machine Translation. Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita, Tiejun Zhao. AAAI 2018. paper

• Multi-Source Syntactic Neural Machine Translation. Anna Currey, Kenneth Heafield. EMNLP 2018. paper

• Incorporating Source Syntax into Transformer-Based Neural Machine Translation. Anna Currey, Kenneth Heafield. WMT 2019. paper

• Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations. Meishan Zhang, Zhenghua Li, Guohong Fu, Min Zhang. NAACL 2019. paper

• Generating Diverse Translations with Sentence Codes. Raphael Shu, Hideki Nakayama, Kyunghyun Cho. ACL 2019. paper code

• Generating Diverse Translation by Manipulating Multi-Head Attention. Zewei Sun, Shujian Huang, Hao-Ran Wei, Xin-yu Dai, Jiajun Chen. AAAI 2020. paper

• Addressing Troublesome Words in Neural Machine Translation. Yang Zhao, Jiajun Zhang, Zhongjun He, Chengqing Zong, and Hua Wu. EMNLP 2018. paper

• Improving Neural Machine Translation with Neural Syntactic Distance. Chunpeng Ma, Akihiro Tamura, Masao Utiyama, Eiichiro Sumita, Tiejun Zhao. NAACL 2019. paper

• Semantic Neural Machine Translation using AMR. Linfeng Song, Daniel Gildea, Yue Zhang, Zhiguo Wang, Jinsong Su. TACL 2019. paper code

• Lattice-Based Recurrent Neural Network Encoders for Neural Machine Translation. Jinsong Su, Zhixing Tan, Deyi Xiong, Rongrong Ji, Xiaodong Shi, Yang Liu. AAAI 2017. paper

• Lattice-Based Transformer Encoder for Neural Machine Translation. Fengshun Xiao, Jiangtong Li, Hai Zhao, Rui Wang, Kehai Chen. ACL 2019. paper

• Pre-trained Language Model Representations for Language Generation. Sergey Edunov, Alexei Baevski, Michael Auli. NAACL 2019. paper code

• MASS: Masked Sequence to Sequence Pre-training for Language Generation. Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, Tie-Yan Liu. ICML 2019. paper code

• Incorporating BERT into Neural Machine Translation. Jinhua Zhu, Yingce Xia, Lijun Wu, Di He, Tao Qin, Wengang Zhou, Houqiang Li, Tieyan Liu. ICLR 2020. paper code

Language + Image:

• Attention Strategies for Multi-Source Sequence-to-Sequence Learning. Jindřich Libovický, Jindřich Helcl. ACL 2017. paper

• Input Combination Strategies for Multi-Source Transformer Decoder. Jindřich Libovický, Jindřich Helcl and David Marecek. WMT 2018. paper

• Doubly-Attentive Decoder for Multi-modal Neural Machine Translation. Iacer Calixto, Qun Liu, Nick Campbell. ACL 2017. paper

• Incorporating Global Visual Features into Attention-based Neural Machine Translation. Iacer Calixto, Qun Liu. EMNLP 2017. paper

• Neural Machine Translation with Universal Visual Representation. Zhuosheng Zhang, Kehai Chen, Rui Wang, Masao Utiyama, Eiichiro Sumita, Zuchao Li, Hai Zhao. ICLR 2020. paper code

• Visual Agreement Regularized Training for Multi-Modal Machine Translation. Pengcheng Yang, Boxing Chen, Pei Zhang, Xu Sun. AAAI 2020. paper

Controling NMT:

• Controlling Politeness in Neural Machine Translation via Side Constraints. Rico Sennrich, Barry Haddow, Alexandra Birch. NAACL 2017. paper

• A Study of Style in Machine Translation: Controlling the Formality of Machine Translation Output. Xing Niu, Marianna Martindale, Marine Carpuat. EMNLP 2017. paper

• Improved Neural Machine Translation using Side Information. Cong Duy Vu Hoang, Gholamreza Haffari, Trevor Cohn. ALTA 1208. paper

• Linguistic Input Features Improve Neural Machine Translation. Rico Sennrich, Barry Haddow. WMT 2016. paper

• Equalizing Gender Biases in Neural Machine Translation with Word Embeddings Techniques. Joel Escudé Font, Marta R. Costa-jussà. ACL WS 2019. paper

Open Vocabulary Problem:

• Addressing the Rare Word Problem in Neural Machine Translation. Minh-Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba. ACL 2015. paper

• On Using Very Large Target Vocabulary for Neural Machine Translation. Sébastien Jean, Kyunghyun Cho, Roland Memisevic, Yoshua Bengio. ACL 2015. paper

• Neural Machine Translation of Rare Words with Subword Units. Rico Sennrich and Barry Haddow and Alexandra Birch. ACL 2016. paper

• Subword Regularization: Improving Neural Network Translation Models with Multiple Subword Candidates. Taku Kudo. ACL 2018. paper

• BPE-Dropout: Simple and Effective Subword Regularization. Ivan Provilkov, Dmitrii Emelianenko, Elena Voita. Arxiv 2018. paper

Evaluation:

• Statistical Significance Tests for Machine Translation Evaluation. Philipp Koehn. EMNLP 2004. paper

• Clause Restructuring for Statistical Machine Translation. Michael Collins, Philipp Koehn, Ivona Kucerova. ACL 2005. paper

• BLEU: a Method for Automatic Evaluation of Machine Translation. Kishore Papineni, Salim Roukos, Todd Ward, Wei-Jing Zhu. ACL 2002. paper

• A Call for Clarity in Reporting BLEU Scores. Matt Post. WMT 2018. paper

• On Evaluation of Adversarial Perturbations for Sequence-to-Sequence Models. Paul Michel, Xian Li, Graham Neubig, Juan Miguel Pino. NAACL 2019. paper

• Adversarial Evaluation of Multimodal Machine Translation. Desmond Elliott. EMNLP 2018. paper

Unsupervised NMT: