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Machine Translation (MT) has greatly advanced over the years due to the developments in deep neural networks.
Language models are few-shot learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 1901
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Future directions of machine translation
Jun’ichi Tsujii. 1986 · 1986
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Toward memory-based translation
Satoshi Sato and Makoto Nagao. 1990 · 1990
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Evaluation of machine translation
John S. White and Theresa A. O’Connell. 1993 · 1993
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Phrase-based statistical machine translation
Richard Zens, Franz Josef Och, and Hermann Ney. 2002 · 2002
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A study of translation edit rate with targeted human annotation
Matthew Snover, Bonnie Dorr, Rich Schwartz, Linnea Micciulla, and John Makhoul. 2006 · 2006
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Moses: Open source toolkit for statistical machine translation
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, et al. 2007 · 2007
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Learning phrase representations using rnn encoder-decoder for statistical machine translation
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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Systran’s pure neural machine translation systems
Josep Maria Crego, Jungi Kim, Guillaume Klein, Anabel Rebollo, Kathy Yang, Jean Senellart, Egor Akhanov, Patrice Brunelle, Aurélien Coquard, Yongchao Deng, Satoshi Enoue, Chiyo Geiss, Joshua Johanson, Ardas Khalsa, Raoum Khiari, Byeongil Ko, Catherine Kobus, Jean Lorieux, Leidiana Martins, Dang-Chuan Nguyen, Alexandra Priori, Thomas Riccardi, Natalia Segal, Christophe Servan, Cyril Tiquet, Bo Wang, Jin Yang, Dakun Zhang, Jing Zhou, and Peter Zoldan. 2016 · 2016
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Neural interactive translation prediction
Rebecca Knowles and Philipp Koehn. 2016 · 2016
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Controlling politeness in neural machine translation via side constraints
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Is neural machine translation the new state of the art?
Sheila Castilho, Joss Moorkens, Federico Gaspari, Iacer Calixto, John Tinsley, and Andy Way. 2017 · 2017
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A challenge set approach to evaluating machine translation
Pierre Isabelle, Colin Cherry, and George Foster. 2017 · 2017
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Six challenges for neural machine translation
Philipp Koehn and Rebecca Knowles. 2017 · 2017
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chrF++: words helping character n-grams
Maja Popović. 2017 · 2017
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Personalized machine translation: Preserving original author traits
Ella Rabinovich, Raj Nath Patel, Shachar Mirkin, Lucia Specia, and Shuly Wintner. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Exploiting cross-sentence context for neural machine translation
Longyue Wang, Zhaopeng Tu, Andy Way, and Qun Liu. 2017 · 2017
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Translating pro-drop languages with reconstruction models
Longyue Wang, Zhaopeng Tu, Shuming Shi, Tong Zhang, Yvette Graham, and Qun Liu. 2018 · 2018
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Unsupervised text style transfer using language models as discriminators
Zichao Yang, Zhiting Hu, Chris Dyer, Eric P Xing, and Taylor Berg-Kirkpatrick. 2018 · 2018
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Neural fuzzy repair: Integrating fuzzy matches into neural machine translation
Bram Bulte and Arda Tezcan. 2019 · 2019
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Training neural machine translation to apply terminology constraints
Georgiana Dinu, Prashant Mathur, Marcello Federico, and Yaser Al-Onaizan. 2019 · 2019
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INMT: Interactive neural machine translation prediction
Sebastin Santy, Sandipan Dandapat, Monojit Choudhury, and Kalika Bali. 2019 · 2019
Cited alongside, same era.
When a good translation is wrong in context: Context-aware machine translation improves on deixis, ellipsis, and lexical cohesion
Elena Voita, Rico Sennrich, and Ivan Titov. 2019 · 2019
Cited alongside, same era.
Discourse-aware neural machine translation
Longyue Wang. 2019 · 2019
Cited alongside, same era.
Assessing human-parity in machine translation on the segment level
Yvette Graham, Christian Federmann, Maria Eskevich, and Barry Haddow. 2020 · 2020
Cited alongside, same era.
Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
Cited alongside, same era.
Controlling neural machine translation formality with synthetic supervision
Prompting palm for translation: Assessing strategies and performance
David Vilar, Markus Freitag, Colin Cherry, Jiaming Luo, Viresh Ratnakar, and George Foster. 2022 · 2022
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GuoFeng: A benchmark for zero pronoun recovery and translation
Longyue Wang, Mingzhou Xu, Derek F. Wong, Hongye Liu, Linfeng Song, Lidia S. Chao, Shuming Shi, and Zhaopeng Tu. 2022a · 2022
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Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M Dai, and Quoc V Le. 2022 · 2022
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Bilingual synchronization: Restoring translational relationships with editing operations
Jitao Xu, Josep Crego, and François Yvon. 2022 · 2022
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Multilingual document-level translation enables zero-shot transfer from sentences to documents
Biao Zhang, Ankur Bapna, Melvin Johnson, Ali Dabirmoghaddam, Naveen Arivazhagan, and Orhan Firat. 2022 · 2022
Later among the works it cites.
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Xing Niu and Marine Carpuat. 2020 · 2020
Cited alongside, same era.
Priming neural machine translation
Minh Quang Pham, Jitao Xu, Josep Crego, François Yvon, and Jean Senellart. 2020 · 2020
Cited alongside, same era.
Neural machine translation: A review
Felix Stahlberg. 2020 · 2020
Cited alongside, same era.
Multimodal machine translation through visuals and speech
Umut Sulubacak, Ozan Caglayan, Stig-Arne Grönroos, Aku Rouhe, Desmond Elliott, Lucia Specia, and Jörg Tiedemann. 2020 · 2020
Cited alongside, same era.
Boosting neural machine translation with similar translations
Jitao Xu, Josep Crego, and Jean Senellart. 2020 · 2020
Cited alongside, same era.
A survey of deep learning techniques for neural machine translation
Shuoheng Yang, Yuxin Wang, and Xiaowen Chu. 2020 · 2020
Cited alongside, same era.
Multimodal transformer for multimodal machine translation
Shaowei Yao and Xiaojun Wan. 2020 · 2020
Cited alongside, same era.
Yejin Bang, Samuel Cahyawijaya, Nayeon Lee, Wenliang Dai, Dan Su, Bryan Wilie, Holy Lovenia, Ziwei Ji, Tiezheng Yu, Willy Chung, et al. 2023 · 2023
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Large language models: A comprehensive survey of its applications, challenges, limitations, and future prospects
Muhammad Usman Hadi, Qasem Al-Tashi, Rizwan Qureshi, Abbas Shah, Amgad Muneer, Muhammad Irfan, Anas Zafar, Muhammad Bilal Shaikh, Naveed Akhtar, Mohammed Ali Al-Garadi, et al. 2023 · 2023
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Exploring human-like translation strategy with large language models
Zhiwei He, Tian Liang, Wenxiang Jiao, Zhuosheng Zhang, Yujiu Yang, Rui Wang, Zhaopeng Tu, Shuming Shi, and Xing Wang. 2023 · 2023
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Large language models are state-of-the-art evaluators of translation quality
Tom Kocmi and Christian Federmann. 2023 · 2023
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A systematic study and comprehensive evaluation of ChatGPT on benchmark datasets
Md Tahmid Rahman Laskar, M Saiful Bari, Mizanur Rahman, Md Amran Hossen Bhuiyan, Shafiq Joty, and Jimmy Huang. 2023 · 2023
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Gpteval: Nlg evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu. 2023 · 2023
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Extrinsic evaluation of machine translation metrics
Nikita Moghe, Tom Sherborne, Mark Steedman, and Alexandra Birch. 2023 · 2023
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Adaptive machine translation with large language models
Yasmin Moslem, Rejwanul Haque, and Andy Way. 2023 · 2023
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OpenAI. 2023 · 2023
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Escaping the sentence-level paradigm in machine translation
Matt Post and Marcin Junczys-Dowmunt. 2023 · 2023
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Chatgpt mt: Competitive for high-(but not low-) resource languages
Nathaniel R Robinson, Perez Ogayo, David R Mortensen, and Graham Neubig. 2023 · 2023
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Focused transformer: Contrastive training for context scaling
Szymon Tworkowski, Konrad Staniszewski, Mikołaj Pacek, Yuhuai Wu, Henryk Michalewski, and Piotr Miłoś. 2023 · 2023
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Document flattening: Beyond concatenating context for document-level neural machine translation
Minghao Wu, George Foster, Lizhen Qu, and Gholamreza Haffari. 2023 · 2023
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Does prompt-tuning language model ensure privacy?
Shangyu Xie, Wei Dai, Esha Ghosh, Sambuddha Roy, Dan Schwartz, and Kim Laine. 2023 · 2023
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Effective long-context scaling of foundation models
Wenhan Xiong, Jingyu Liu, Igor Molybog, Hejia Zhang, Prajjwal Bhargava, Rui Hou, Louis Martin, Rashi Rungta, Karthik Abinav Sankararaman, Barlas Oguz, Madian Khabsa, Han Fang, Yashar Mehdad, Sharan Narang, Kshitiz Malik, Angela Fan, Shruti Bhosale, Sergey Edunov, Mike Lewis, Sinong Wang, and Hao Ma. 2023 · 2023
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Multilingual machine translation with large language models: Empirical results and analysis
Wenhao Zhu, Hongyi Liu, Qingxiu Dong, Jingjing Xu, Lingpeng Kong, Jiajun Chen, Lei Li, and Shujian Huang. 2023 · 2023
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Salute the classic: Revisiting challenges of machine translation in the age of large language models
Jianhui Pang, Fanghua Ye, Longyue Wang, Dian Yu, Derek F Wong, Shuming Shi, and Zhaopeng Tu. 2024 · 2024
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Personalized machine translation: Predicting translational preferences
Shachar Mirkin and Jean-Luc Meunier. 2015 · 2025
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