--- title: "Machine translation — library papers" description: "Machine translation: 386 papers of the Elamur Research library on it, the most cited first — each with our summary, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/topics/machine-translation/library/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/topics/machine-translation/library/) [home](https://md.research.elamur.ai/free/en/) / [topics](https://md.research.elamur.ai/free/en/topics/) / [Machine translation](https://md.research.elamur.ai/free/en/topics/machine-translation/) / library # Machine translation — papers in the library 386 papers · [the topic and Mova's cards](https://md.research.elamur.ai/free/en/topics/machine-translation/) **1** [2](https://md.research.elamur.ai/free/en/topics/machine-translation/library/page/2/) [3](https://md.research.elamur.ai/free/en/topics/machine-translation/library/page/3/) [4](https://md.research.elamur.ai/free/en/topics/machine-translation/library/page/4/) - [Neural Machine Translation by Jointly Learning to Align and Translate](https://md.research.elamur.ai/free/en/papers/bahdanau-2014-neural-machine-translation-jointly-learning/) — Dzmitry Bahdanau, Kyunghyun Cho, Yoshua Bengio · arXiv:1409.0473 - [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://md.research.elamur.ai/free/en/papers/kudo-2018-sentencepiece-simple-language-independent-subword/) — Taku Kudo, John Richardson · Proceedings of the 2018 Conference on Empirical… - [Evaluating Large Language Models Trained on Code](https://md.research.elamur.ai/free/en/papers/chen-2021-evaluating-large-language-models-trained/) — Mark Chen, Jerry Tworek, Heewoo Jun, et al. · arXiv:2107.03374 - [A Diversity-Promoting Objective Function for Neural Conversation Models](https://md.research.elamur.ai/free/en/papers/li-2016-diversity-promoting-objective-function-neural/) — Jiwei Li, Michel Galley, Chris Brockett, et al. · Proceedings of the 2016 Conference of the North… - [On the Properties of Neural Machine Translation: Encoder-Decoder Approaches](https://md.research.elamur.ai/free/en/papers/cho-2014-properties-neural-machine-translation-encoder/) — Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau, et al. · arXiv:1409.1259 - [OpenNMT: Open-Source Toolkit for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/klein-2017-opennmt-open-source-toolkit-neural/) — Guillaume Klein, Yoon Kim, Yuntian Deng, et al. · Proceedings of ACL 2017, System Demonstrations - [Sequence-Level Knowledge Distillation](https://md.research.elamur.ai/free/en/papers/kim-2016-sequence-level-knowledge-distillation/) — Yoon Kim, Alexander M. Rush · Proceedings of the 2016 Conference on Empirical… - [Convolutional Sequence to Sequence Learning](https://md.research.elamur.ai/free/en/papers/gehring-2017-convolutional-sequence-sequence-learning/) — Jonas Gehring, Michael Auli, David Grangier, et al. · arXiv:1705.03122 - [KenLM: Faster and Smaller Language Model Queries](https://md.research.elamur.ai/free/en/papers/heafield-2011-kenlm-faster-smaller-language-model/) — Kenneth Heafield · Proceedings of the Sixth Workshop on… - [Meteor Universal: Language Specific Translation Evaluation for Any Target Language](https://md.research.elamur.ai/free/en/papers/denkowski-2014-meteor-universal-language-specific-translation/) — Michael Denkowski, Alon Lavie · Proceedings of the Ninth Workshop on… - [Self-Attention with Relative Position Representations](https://md.research.elamur.ai/free/en/papers/shaw-2018-self-attention-relative-position-representations/) — Peter Shaw, Jakob Uszkoreit, Ashish Vaswani · Proceedings of the 2018 Conference of the North… - [Sequence Level Training with Recurrent Neural Networks](https://md.research.elamur.ai/free/en/papers/ranzato-2015-sequence-level-training-recurrent-neural/) — Marc'Aurelio Ranzato, Sumit Chopra, Michael Auli, et al. · arXiv:1511.06732 - [Discriminative Training and Maximum Entropy Models for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/och-2002-discriminative-training-maximum-entropy-models/) — Franz Josef Och, Hermann Ney · Proceedings of the 40th Annual Meeting of the… - [OpenSubtitles2016: Extracting Large Parallel Corpora from Movie and TV Subtitles](https://md.research.elamur.ai/free/en/papers/lison-2016-opensubtitles2016-extracting-large-parallel-corpora/) — Pierre Lison, Jörg Tiedemann · Proceedings of the Tenth International… - [Findings of the 2014 Workshop on Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/bojar-2014-findings-2014-workshop-statistical-machine/) — Ondřej Bojar, Christian Buck, Christian Federmann, et al. · Proceedings of the Ninth Workshop on… - [Analyzing Multi-Head Self-Attention: Specialized Heads Do the Heavy Lifting, the Rest Can Be Pruned](https://md.research.elamur.ai/free/en/papers/voita-2019-analyzing-multi-head-self-attention/) — Elena Voita, David Talbot, Fedor Moiseev, et al. · arXiv:1905.09418 - [Microsoft COCO Captions: Data Collection and Evaluation Server](https://md.research.elamur.ai/free/en/papers/chen-2015-microsoft-coco-captions-data-collection/) — Xinlei Chen, Hao Fang, Tsung-Yi Lin, et al. · arXiv:1504.00325 - [Unsupervised Machine Translation Using Monolingual Corpora Only](https://md.research.elamur.ai/free/en/papers/lample-2017-unsupervised-machine-translation-using-monolingual/) — Guillaume Lample, Alexis Conneau, Ludovic Denoyer, et al. · arXiv:1711.00043 - [Show and Tell: A Neural Image Caption Generator](https://md.research.elamur.ai/free/en/papers/vinyals-2014-show-tell-neural-image-caption/) — Oriol Vinyals, Alexander Toshev, Samy Bengio, et al. · arXiv:1411.4555 - [MASS: Masked Sequence to Sequence Pre-training for Language Generation](https://md.research.elamur.ai/free/en/papers/song-2019-mass-masked-sequence-sequence-pre/) — Kaitao Song, Xu Tan, Tao Qin, et al. · arXiv:1905.02450 - [Findings of the 2016 Conference on Machine Translation](https://md.research.elamur.ai/free/en/papers/bojar-2016-findings-2016-conference-machine-translation/) — Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al. · Proceedings of the First Conference on Machine… - [Findings of the 2019 Conference on Machine Translation (WMT19)](https://md.research.elamur.ai/free/en/papers/barrault-2019-findings-2019-conference-machine-translation/) — Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, et al. · Proceedings of the Fourth Conference on Machine… - [Marian: Fast Neural Machine Translation in C++](https://md.research.elamur.ai/free/en/papers/junczys-2018-dowmunt-marian-fast-neural-machine-translation/) — Marcin Junczys-Dowmunt, Roman Grundkiewicz, Tomasz Dwojak, et al. · arXiv:1804.00344 - [Clause Restructuring for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/collins-2005-clause-restructuring-statistical-machine-translation/) — Michael Collins, Philipp Koehn, Ivona Kučerová · Proceedings of the 43rd Annual Meeting of the… - [Evaluating Gender Bias in Machine Translation](https://md.research.elamur.ai/free/en/papers/stanovsky-2019-evaluating-gender-bias-machine-translation/) — Gabriel Stanovsky, Noah A. Smith, Luke Zettlemoyer · Proceedings of the 57th Annual Meeting of the… - [Achieving Human Parity on Automatic Chinese to English News Translation](https://md.research.elamur.ai/free/en/papers/hassan-2018-achieving-human-parity-automatic-chinese/) — Hany Hassan, Anthony Aue, Chang Chen, et al. · arXiv:1803.05567 - [Unsupervised Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/artetxe-2017-unsupervised-neural-machine-translation/) — Mikel Artetxe, Gorka Labaka, Eneko Agirre, et al. · arXiv:1710.11041 - [Measuring Coding Challenge Competence With APPS](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-measuring-coding-challenge-competence-apps/) — Dan Hendrycks, Steven Basart, Saurav Kadavath, et al. · arXiv:2105.09938 - [Massively Multilingual Neural Machine Translation in the Wild: Findings and Challenges](https://md.research.elamur.ai/free/en/papers/arivazhagan-2019-massively-multilingual-neural-machine-translation/) — Naveen Arivazhagan, Ankur Bapna, Orhan Firat, et al. · arXiv:1907.05019 - [Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine](https://md.research.elamur.ai/free/en/papers/jiao-2023-chatgpt-good-translator-yes-gpt/) — Wenxiang Jiao, Wenxuan Wang, Jen-tse Huang, et al. · arXiv:2301.08745 - [Multilingual Machine Translation with Large Language Models: Empirical Results and Analysis](https://md.research.elamur.ai/free/en/papers/zhu-2024-multilingual-machine-translation-large-language/) — Wenhao Zhu, Hongyi Liu, Qingxiu Dong, et al. · Findings of the Association for Computational… - [Non-Autoregressive Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/gu-2017-non-autoregressive-neural-machine-translation/) — Jiatao Gu, James Bradbury, Caiming Xiong, et al. · arXiv:1711.02281 - [Using the Output Embedding to Improve Language Models](https://md.research.elamur.ai/free/en/papers/press-2017-output-embedding-improve-language-models/) — Ofir Press, Lior Wolf · Proceedings of the 15th Conference of the… - [Domain Adaptation via Pseudo In-Domain Data Selection](https://md.research.elamur.ai/free/en/papers/axelrod-2011-domain-adaptation-pseudo-domain-data/) — Amittai Axelrod, Xiaodong He, Jianfeng Gao · Proceedings of the 2011 Conference on Empirical… - [Findings of the 2017 Conference on Machine Translation (WMT17)](https://md.research.elamur.ai/free/en/papers/bojar-2017-findings-2017-conference-machine-translation/) — Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al. · Proceedings of the Second Conference on Machine… - [xCOMET: Transparent Machine Translation Evaluation through Fine-grained Error Detection](https://md.research.elamur.ai/free/en/papers/guerreiro-2024-xcomet-transparent-machine-translation-evaluation/) — Nuno M. Guerreiro, Ricardo Rei, Daan van Stigt, et al. · Transactions of the Association for… - [Neural Responding Machine for Short-Text Conversation](https://md.research.elamur.ai/free/en/papers/shang-2015-neural-responding-machine-short-text/) — Lifeng Shang, Zhengdong Lu, Hang Li · Proceedings of the 53rd Annual Meeting of the… - [Scaling Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/ott-2018-scaling-neural-machine-translation/) — Myle Ott, Sergey Edunov, David Grangier, et al. · Proceedings of the Third Conference on Machine… - [Massively Multilingual Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/aharoni-2019-massively-multilingual-neural-machine-translation/) — Roee Aharoni, Melvin Johnson, Orhan Firat · arXiv:1903.00089 - [Multi-Way, Multilingual Neural Machine Translation with a Shared Attention Mechanism](https://md.research.elamur.ai/free/en/papers/firat-2016-multi-way-multilingual-neural-machine/) — Orhan Firat, Kyunghyun Cho, Yoshua Bengio · Proceedings of the 2016 Conference of the North… - [Minimum Bayes-Risk Decoding for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/kumar-2004-minimum-bayes-risk-decoding-statistical/) — Shankar Kumar, William Byrne · Proceedings of the Human Language Technology… - [Prompt Programming for Large Language Models: Beyond the Few-Shot Paradigm](https://md.research.elamur.ai/free/en/papers/reynolds-2021-prompt-programming-large-language-models/) — Laria Reynolds, Kyle McDonell · arXiv:2102.07350 - [The United Nations Parallel Corpus v1.0](https://md.research.elamur.ai/free/en/papers/ziemski-2016-united-nations-parallel-corpus-v1/) — Michał Ziemski, Marcin Junczys-Dowmunt, Bruno Pouliquen · Proceedings of the Tenth International… - [Neural Text Generation from Structured Data with Application to the Biography Domain](https://md.research.elamur.ai/free/en/papers/lebret-2016-neural-text-generation-structured-data/) — Remi Lebret, David Grangier, Michael Auli · arXiv:1603.07771 - [Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation](https://md.research.elamur.ai/free/en/papers/zhang-2020-improving-massively-multilingual-neural-machine/) — Biao Zhang, Philip Williams, Ivan Titov, et al. · Proceedings of the 58th Annual Meeting of the… - [Modeling Coverage for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/tu-2016-modeling-coverage-neural-machine-translation/) — Zhaopeng Tu, Zhengdong Lu, Yang Liu, et al. · Proceedings of the 54th Annual Meeting of the… - [Style Transfer Through Back-Translation](https://md.research.elamur.ai/free/en/papers/prabhumoye-2018-style-transfer-through-back-translation/) — Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, et al. · Proceedings of the 56th Annual Meeting of the… - [Facebook FAIR's WMT19 News Translation Task Submission](https://md.research.elamur.ai/free/en/papers/ng-2019-facebook-fair-s-wmt19-news/) — Nathan Ng, Kyra Yee, Alexei Baevski, et al. · Proceedings of the Fourth Conference on Machine… - [Learning to Ask: Neural Question Generation for Reading Comprehension](https://md.research.elamur.ai/free/en/papers/du-2017-learning-ask-neural-question-generation/) — Xinya Du, Junru Shao, Claire Cardie · arXiv:1705.00106 - [Findings of the 2018 Conference on Machine Translation (WMT18)](https://md.research.elamur.ai/free/en/papers/bojar-2018-findings-2018-conference-machine-translation/) — Ondřej Bojar, Christian Federmann, Mark Fishel, et al. · Proceedings of the Third Conference on Machine… - [CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB](https://md.research.elamur.ai/free/en/papers/schwenk-2019-ccmatrix-mining-billions-high-quality/) — Holger Schwenk, Guillaume Wenzek, Sergey Edunov, et al. · arXiv:1911.04944 - [Multi-Task Learning for Multiple Language Translation](https://md.research.elamur.ai/free/en/papers/dong-2015-multi-task-learning-multiple-language/) — Daxiang Dong, Hua Wu, Wei He, et al. · Proceedings of the 53rd Annual Meeting of the… - [Automatic Evaluation of Machine Translation Quality Using Longest Common Subsequence and Skip-Bigram Statistics](https://md.research.elamur.ai/free/en/papers/lin-2004-automatic-evaluation-machine-translation-quality/) — Chin-Yew Lin, Franz Josef Och · Proceedings of the 42nd Annual Meeting of the… - [Collecting Highly Parallel Data for Paraphrase Evaluation](https://md.research.elamur.ai/free/en/papers/chen-2011-collecting-highly-parallel-data-paraphrase/) — David Chen, William Dolan · Proceedings of the 49th Annual Meeting of the… - [Simple, Scalable Adaptation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/bapna-2019-simple-scalable-adaptation-neural-machine/) — Ankur Bapna, Orhan Firat · Proceedings of the 2019 Conference on Empirical… - [Mask-Predict: Parallel Decoding of Conditional Masked Language Models](https://md.research.elamur.ai/free/en/papers/ghazvininejad-2019-mask-predict-parallel-decoding-conditional/) — Marjan Ghazvininejad, Omer Levy, Yinhan Liu, et al. · Proceedings of the 2019 Conference on Empirical… - [Controlling Politeness in Neural Machine Translation via Side Constraints](https://md.research.elamur.ai/free/en/papers/sennrich-2016-controlling-politeness-neural-machine-translation/) — Rico Sennrich, Barry Haddow, Alexandra Birch · Proceedings of the 2016 Conference of the North… - [Factored Translation Models](https://md.research.elamur.ai/free/en/papers/koehn-2007-factored-translation-models/) — Philipp Koehn, Hieu Hoang · Proceedings of the 2007 Joint Conference on… - [Findings of the 2013 Workshop on Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/bojar-2013-findings-2013-workshop-statistical-machine/) — Ondřej Bojar, Christian Buck, Chris Callison-Burch, et al. · Proceedings of the Eighth Workshop on… - [Does String-Based Neural MT Learn Source Syntax?](https://md.research.elamur.ai/free/en/papers/shi-2016-does-string-based-neural-mt/) — Xing Shi, Inkit Padhi, Kevin Knight · Proceedings of the 2016 Conference on Empirical… - [What do Neural Machine Translation Models Learn about Morphology?](https://md.research.elamur.ai/free/en/papers/belinkov-2017-what-do-neural-machine-translation/) — Yonatan Belinkov, Nadir Durrani, Fahim Dalvi, et al. · Proceedings of the 55th Annual Meeting of the… - [ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations](https://md.research.elamur.ai/free/en/papers/wieting-2018-paranmt-50m-pushing-limits-paraphrastic/) — John Wieting, Kevin Gimpel · Proceedings of the 56th Annual Meeting of the… - [Meteor 1.3: Automatic Metric for Reliable Optimization and Evaluation of Machine Translation Systems](https://md.research.elamur.ai/free/en/papers/denkowski-2011-meteor-1-3-automatic-metric/) — Michael Denkowski, Alon Lavie · Proceedings of the Sixth Workshop on… - [Edinburgh Neural Machine Translation Systems for WMT 16](https://md.research.elamur.ai/free/en/papers/sennrich-2016-edinburgh-neural-machine-translation-systems/) — Rico Sennrich, Barry Haddow, Alexandra Birch · Proceedings of the First Conference on Machine… - [Findings of the 2020 Conference on Machine Translation (WMT20)](https://md.research.elamur.ai/free/en/papers/barrault-2020-findings-2020-conference-machine-translation/) — Loïc Barrault, Magdalena Biesialska, Ondřej Bojar, et al. · Proceedings of the Fifth Conference on Machine… - [WikiMatrix: Mining 135M Parallel Sentences in 1620 Language Pairs from Wikipedia](https://md.research.elamur.ai/free/en/papers/schwenk-2019-wikimatrix-mining-135m-parallel-sentences/) — Holger Schwenk, Vishrav Chaudhary, Shuo Sun, et al. · arXiv:1907.05791 - [Addressing the Rare Word Problem in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/luong-2015-addressing-rare-word-problem-neural/) — Thang Luong, Ilya Sutskever, Quoc Le, et al. · Proceedings of the 53rd Annual Meeting of the… - [Findings of the 2015 Workshop on Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/bojar-2015-findings-2015-workshop-statistical-machine/) — Ondřej Bojar, Rajen Chatterjee, Christian Federmann, et al. · Proceedings of the Tenth Workshop on… - [On Using Very Large Target Vocabulary for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/jean-2015-very-large-target-vocabulary-neural/) — Sébastien Jean, Kyunghyun Cho, Roland Memisevic, et al. · Proceedings of the 53rd Annual Meeting of the… - [Prompting Large Language Model for Machine Translation: A Case Study](https://md.research.elamur.ai/free/en/papers/zhang-2023-prompting-large-language-model-machine/) — Biao Zhang, Barry Haddow, Alexandra Birch · arXiv:2301.07069 - [A Neural Network Approach to Context-Sensitive Generation of Conversational Responses](https://md.research.elamur.ai/free/en/papers/sordoni-2015-neural-network-approach-context-sensitive/) — Alessandro Sordoni, Michel Galley, Michael Auli, et al. · arXiv:1506.06714 - [Improved Alignment Models for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/och-1999-improved-alignment-models-statistical-machine/) — Franz Josef Och, Christoph Tillmann, Hermann Ney · 1999 Joint SIGDAT Conference on Empirical… - [A Phrase-Based,Joint Probability Model for Statistical Machine Translation](https://md.research.elamur.ai/free/en/papers/marcu-2002-phrase-based-joint-probability-model/) — Daniel Marcu, Daniel Wong · Proceedings of the 2002 Conference on Empirical… - [Automatic Evaluation of Translation Quality for Distant Language Pairs](https://md.research.elamur.ai/free/en/papers/isozaki-2010-automatic-evaluation-translation-quality-distant/) — Hideki Isozaki, Tsutomu Hirao, Kevin Duh, et al. · Proceedings of the 2010 Conference on Empirical… - [Minimum Risk Training for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/shen-2015-minimum-risk-training-neural-machine/) — Shiqi Shen, Yong Cheng, Zhongjun He, et al. · arXiv:1512.02433 - [Fast Lexically Constrained Decoding with Dynamic Beam Allocation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/post-2018-fast-lexically-constrained-decoding-dynamic/) — Matt Post, David Vilar · Proceedings of the 2018 Conference of the North… - [Edinburgh System Description for the 2005 IWSLT Speech Translation Evaluation](https://md.research.elamur.ai/free/en/papers/koehn-2005-edinburgh-system-description-2005-iwslt/) — Philipp Koehn, Amittai Axelrod, Alexandra Birch Mayne, et al. · Proceedings of the Second International… - [Context-Aware Neural Machine Translation Learns Anaphora Resolution](https://md.research.elamur.ai/free/en/papers/voita-2018-context-aware-neural-machine-translation/) — Elena Voita, Pavel Serdyukov, Rico Sennrich, et al. · Proceedings of the 56th Annual Meeting of the… - [Data Augmentation for Low-Resource Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/fadaee-2017-data-augmentation-low-resource-neural/) — Marzieh Fadaee, Arianna Bisazza, Christof Monz · Proceedings of the 55th Annual Meeting of the… - [Large Language Models in Machine Translation](https://md.research.elamur.ai/free/en/papers/brants-2007-large-language-models-machine-translation/) — Thorsten Brants, Ashok C. Popat, Peng Xu, et al. · Proceedings of the 2007 Joint Conference on… - [Evaluating Discourse Phenomena in Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/bawden-2017-evaluating-discourse-phenomena-neural-machine/) — Rachel Bawden, Rico Sennrich, Alexandra Birch, et al. · arXiv:1711.00513 - [Has Machine Translation Achieved Human Parity? A Case for Document-level Evaluation](https://md.research.elamur.ai/free/en/papers/laubli-2018-has-machine-translation-achieved-human/) — Samuel Läubli, Rico Sennrich, Martin Volk · Proceedings of the 2018 Conference on Empirical… - [Iterative Back-Translation for Neural Machine Translation](https://md.research.elamur.ai/free/en/papers/hoang-2018-iterative-back-translation-neural-machine/) — Vu Cong Duy Hoang, Philipp Koehn, Gholamreza Haffari, et al. · Proceedings of the 2nd Workshop on Neural… - [The FLORES Evaluation Datasets for Low-Resource Machine Translation: Nepali–English and Sinhala–English](https://md.research.elamur.ai/free/en/papers/guzman-2019-flores-evaluation-datasets-low-resource/) — Francisco Guzmán, Peng-Jen Chen, Myle Ott, et al. · Proceedings of the 2019 Conference on Empirical… - [Exploring Neural Text Simplification Models](https://md.research.elamur.ai/free/en/papers/nisioi-2017-exploring-neural-text-simplification-models/) — Sergiu Nisioi, Sanja Štajner, Simone Paolo Ponzetto, et al. · Proceedings of the 55th Annual Meeting of the… - [Syntax Augmented Machine Translation via Chart Parsing](https://md.research.elamur.ai/free/en/papers/zollmann-2006-syntax-augmented-machine-translation-chart/) — Andreas Zollmann, Ashish Venugopal · Proceedings on the Workshop on Statistical… - [When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?](https://md.research.elamur.ai/free/en/papers/qi-2018-when-why-are-pre-trained/) — Ye Qi, Devendra Sachan, Matthieu Felix, et al. · Proceedings of the 2018 Conference of the North… - [Forest Rescoring: Faster Decoding with Integrated Language Models](https://md.research.elamur.ai/free/en/papers/huang-2007-forest-rescoring-faster-decoding-integrated/) — Liang Huang, David Chiang · Proceedings of the 45th Annual Meeting of the… - [BPE-Dropout: Simple and Effective Subword Regularization](https://md.research.elamur.ai/free/en/papers/provilkov-2020-bpe-dropout-simple-effective-subword/) — Ivan Provilkov, Dmitrii Emelianenko, Elena Voita · Proceedings of the 58th Annual Meeting of the… - [Manual and Automatic Evaluation of Machine Translation between European Languages](https://md.research.elamur.ai/free/en/papers/koehn-2006-manual-automatic-evaluation-machine-translation/) — Philipp Koehn, Christof Monz · Proceedings on the Workshop on Statistical… - [Improving Machine Translation Performance by Exploiting Non-Parallel Corpora](https://md.research.elamur.ai/free/en/papers/munteanu-2005-improving-machine-translation-performance-exploiting/) — Dragos Stefan Munteanu, Daniel Marcu · Computational Linguistics - [Unsupervised Construction of Large Paraphrase Corpora: Exploiting Massively Parallel News Sources](https://md.research.elamur.ai/free/en/papers/dolan-2004-unsupervised-construction-large-paraphrase-corpora/) — Bill Dolan, Chris Quirk, Chris Brockett · COLING 2004: Proceedings of the 20th… - [Learning Deep Transformer Models for Machine Translation](https://md.research.elamur.ai/free/en/papers/wang-2019-learning-deep-transformer-models-machine/) — Qiang Wang, Bei Li, Tong Xiao, et al. · Proceedings of the 57th Annual Meeting of the… - [When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical Cohesion](https://md.research.elamur.ai/free/en/papers/voita-2019-when-good-translation-is-wrong/) — Elena Voita, Rico Sennrich, Ivan Titov · Proceedings of the 57th Annual Meeting of the… - [Toward Multilingual Neural Machine Translation with Universal Encoder and Decoder](https://md.research.elamur.ai/free/en/papers/ha-2016-multilingual-neural-machine-translation-universal/) — Thanh-Le Ha, Jan Niehues, Alex Waibel · Proceedings of the 13th International… - [In-context Examples Selection for Machine Translation](https://md.research.elamur.ai/free/en/papers/agrawal-2023-context-examples-selection-machine-translation/) — Sweta Agrawal, Chunting Zhou, Mike Lewis, et al. · Findings of the Association for Computational… - [Fully Character-Level Neural Machine Translation without Explicit Segmentation](https://md.research.elamur.ai/free/en/papers/lee-2017-fully-character-level-neural-machine/) — Jason Lee, Kyunghyun Cho, Thomas Hofmann · Transactions of the Association for… - 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