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Multilingual machine translation enables a single model to translate between different languages.
RoBERTa: A robustly optimized BERT pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
Earlier work this paper cites.
Deep encoder, shallow decoder: Reevaluating the speed-quality tradeoff in machine translation
Jungo Kasai, Nikolaos Pappas, Hao Peng, James Cross, and Noah A. Smith. 2020 · 2006
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GShard: Scaling giant models with conditional computation and automatic sharding
Dmitry Lepikhin, HyoukJoong Lee, Yuanzhong Xu, Dehao Chen, Orhan Firat, Yanping Huang, Maxim Krikun, Noam Shazeer, and Zhifeng Chen. 2020 · 2006
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InfoXLM: An information-theoretic framework for cross-lingual language model pre-training
Zewen Chi, Li Dong, Furu Wei, Nan Yang, Saksham Singhal, Wenhui Wang, Xia Song, Xian-Ling Mao, Heyan Huang, and Ming Zhou. 2020b · 2007
Earlier work this paper cites.
Multilingual translation with extensible multilingual pretraining and finetuning
Yuqing Tang, Chau Tran, Xian Li, Peng-Jen Chen, Naman Goyal, Vishrav Chaudhary, Jiatao Gu, and Angela Fan. 2020 · 2008
Earlier work this paper cites.
Beyond english-centric multilingual machine translation
Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky, Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin. 2020 · 2010
Earlier work this paper cites.
mT5: A massively multilingual pre-trained text-to-text transformer
Linting Xue, Noah Constant, Adam Roberts, Mihir Kale, Rami Al-Rfou, Aditya Siddhant, Aditya Barua, and Colin Raffel. 2020 · 2010
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Multi-way, multilingual neural machine translation with a shared attention mechanism
Orhan Firat, Kyunghyun Cho, and Yoshua Bengio. 2016a · 2016
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Zero-resource translation with multi-lingual neural machine translation
Orhan Firat, Baskaran Sankaran, Yaser Al-Onaizan, Fatos T. Yarman-Vural, and Kyunghyun Cho. 2016b · 2016
Earlier work this paper cites.
Toward multilingual neural machine translation with universal encoder and decoder
Thanh-Le Ha, Jan Niehues, and Alexander H. Waibel. 2016 · 2016
Earlier work this paper cites.
Bridging nonlinearities and stochastic regularizers with gaussian error linear units
Dan Hendrycks and Kevin Gimpel. 2016 · 2016
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Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Earlier work this paper cites.
Transfer learning for low-resource neural machine translation
Barret Zoph, Deniz Yuret, Jonathan May, and Kevin Knight. 2016 · 2016
Earlier work this paper cites.
Google’s multilingual neural machine translation system: Enabling zero-shot translation
Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda B. Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2017 · 2017
Cited alongside, same era.
Multilingual neural machine translation with task-specific attention
Graeme Blackwood, Miguel Ballesteros, and Todd Ward. 2018 · 2018
Cited alongside, same era.
Universal neural machine translation for extremely low resource languages
Jiatao Gu, Hany Hassan, Jacob Devlin, and Victor O. K. Li. 2018 · 2018
Cited alongside, same era.
SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
Cited alongside, same era.
Contextual parameter generation for universal neural machine translation
Emmanouil Antonios Platanios, Mrinmaya Sachan, Graham Neubig, and Tom M. Mitchell. 2018 · 2018
Cited alongside, same era.
Multilingual unsupervised NMT using shared encoder and language-specific decoders
Sukanta Sen, Kamal Kumar Gupta, Asif Ekbal, and Pushpak Bhattacharyya. 2019 · 2019
Later among the works it cites.
MASS: masked sequence to sequence pre-training for language generation
Kaitao Song, Xu Tan, Tao Qin, Jianfeng Lu, and Tie-Yan Liu. 2019 · 2019
Later among the works it cites.
XLNet: Generalized autoregressive pretraining for language understanding
Zhilin Yang, Zihang Dai, Yiming Yang, Jaime G. Carbonell, Ruslan Salakhutdinov, and Quoc V. Le. 2019 · 2019
Later among the works it cites.
UniLMv2: Pseudo-masked language models for unified language model pre-training
Hangbo Bao, Li Dong, Furu Wei, Wenhui Wang, Nan Yang, Xiaodong Liu, Yu Wang, Jianfeng Gao, Songhao Piao, Ming Zhou, and Hsiao-Wuen Hon. 2020 · 2020
Closest in time.
Cross-lingual natural language generation via pre-training
Zewen Chi, Li Dong, Furu Wei, Wenhui Wang, Xian-Ling Mao, and Heyan Huang. 2020a · 2020
Closest in time.
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
Cited alongside, same era.
An analysis of encoder representations in transformer-based machine translation
Alessandro Raganato and Jörg Tiedemann. 2018 · 2018
Cited alongside, same era.
Massively multilingual neural machine translation
Roee Aharoni, Melvin Johnson, and Orhan Firat. 2019 · 2019
Cited alongside, same era.
Cross-lingual language model pretraining
Alexis Conneau and Guillaume Lample. 2019 · 2019
Cited alongside, same era.
BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Cited alongside, same era.
Unified language model pre-training for natural language understanding and generation
Li Dong, Nan Yang, Wenhui Wang, Furu Wei, Xiaodong Liu, Yu Wang, Jianfeng Gao, Ming Zhou, and Hsiao-Wuen Hon. 2019 · 2019
Cited alongside, same era.
Visualizing and understanding the effectiveness of BERT
Yaru Hao, Li Dong, Furu Wei, and Ke Xu. 2019 · 2019
Cited alongside, same era.
Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
Closest in time.
BART: denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Veselin Stoyanov, and Luke Zettlemoyer. 2020 · 2020
Closest in time.
Pre-training multilingual neural machine translation by leveraging alignment information
Zehui Lin, Xiao Pan, Mingxuan Wang, Xipeng Qiu, Jiangtao Feng, Hao Zhou, and Lei Li. 2020 · 2020
Closest in time.
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
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2020 · 2020
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SimAlign: High quality word alignments without parallel training data using static and contextualized embeddings
Masoud Jalili Sabet, Philipp Dufter, François Yvon, and Hinrich Schütze. 2020 · 2020
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Multi-task learning for multilingual neural machine translation
Yiren Wang, ChengXiang Zhai, and Hany Hassan. 2020 · 2020
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CCNet: Extracting high quality monolingual datasets from web crawl data
Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzmán, Armand Joulin, and Edouard Grave. 2020 · 2020
Closest in time.
Improving massively multilingual neural machine translation and zero-shot translation
Biao Zhang, Philip Williams, Ivan Titov, and Rico Sennrich. 2020 · 2020
Closest in time.