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While achieving state-of-the-art results in multiple tasks and languages, translation-based cross-lingual transfer is often overlooked in favour of massively multilingual pre-trained encoders.
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
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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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Minimum error rate training in statistical machine translation
Franz Josef Och. 2003 · 2003
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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Minimum risk annealing for training log-linear models
David A. Smith and Jason Eisner. 2006 · 2006
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Multilingual subjectivity analysis using machine translation
Carmen Banea, Rada Mihalcea, Janyce Wiebe, and Samer Hassan. 2008 · 2008
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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
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A unified approach to minimum risk training and decoding
Abhishek Arun, Barry Haddow, and Philipp Koehn. 2010 · 2010
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Syntactic transfer using a bilingual lexicon
Greg Durrett, Adam Pauls, and Dan Klein. 2012 · 2012
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How good is your tokenizer? on the monolingual performance of multilingual language models
Phillip Rust, Jonas Pfeiffer, Ivan Vulić, Sebastian Ruder, and Iryna Gurevych. 2020 · 2012
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A closer look at few-shot crosslingual transfer: Variance, benchmarks and baselines
Mengjie Zhao, Yi Zhu, Ehsan Shareghi, Roi Reichart, Anna Korhonen, and Hinrich Schütze. 2020 · 2012
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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville. 2013 · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Techniques for learning binary stochastic feedforward neural networks
Tapani Raiko, Mathias Berglund, Guillaume Alain, and Laurent Dinh. 2014 · 2014
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Learning to translate queries for clir
Artem Sokolov, Felix Hieber, and Stefan Riezler. 2014 · 2014
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Dual learning for machine translation
Di He, Yingce Xia, Tao Qin, Liwei Wang, Nenghai Yu, Tie-Yan Liu, and Wei-Ying Ma. 2016 · 2016
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Sequence level training with recurrent neural networks
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2016 · 2016
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Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Minimum risk training for neural machine translation
Shiqi Shen, Yong Cheng, Zhongjun He, Wei He, Hua Wu, Maosong Sun, and Yang Liu. 2016 · 2016
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Sequence-to-sequence learning as beam-search optimization
Sam Wiseman and Alexander M. Rush. 2016 · 2016
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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, et al. 2016 · 2016
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Learning to paraphrase for question answering
Li Dong, Jonathan Mallinson, Siva Reddy, and Mirella Lapata. 2017 · 2017
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Categorical reparameterization with Gumbel-Softmax
Eric Jang, Shixiang Gu, and Ben Poole. 2017 · 2017
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Beyond BLEU:training neural machine translation with semantic similarity
John Wieting, Taylor Berg-Kirkpatrick, Kevin Gimpel, and Graham Neubig. 2019 · 2019
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Beto, bentz, becas: The surprising cross-lingual effectiveness of BERT
Shijie Wu and Mark Dredze. 2019 · 2019
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PAWS-X: A cross-lingual adversarial dataset for paraphrase identification
Yinfei Yang, Yuan Zhang, Chris Tar, and Jason Baldridge. 2019 · 2019
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Translation artifacts in cross-lingual transfer learning
Mikel Artetxe, Gorka Labaka, and Eneko Agirre. 2020 · 2020
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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
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Chris J Maddison, Andriy Mnih, and Yee Whye Teh. 2017 · 2017
Cited alongside, same era.
XNLI: Evaluating cross-lingual sentence representations
Alexis Conneau, Ruty Rinott, Guillaume Lample, Adina Williams, Samuel Bowman, Holger Schwenk, and Veselin Stoyanov. 2018 · 2018
Cited alongside, same era.
Classical structured prediction losses for sequence to sequence learning
Sergey Edunov, Myle Ott, Michael Auli, David Grangier, and Marc’Aurelio Ranzato. 2018 · 2018
Cited alongside, same era.
Zero-shot cross-lingual classification using multilingual neural machine translation
Akiko Eriguchi, Melvin Johnson, Orhan Firat, Hideto Kazawa, and Wolfgang Macherey. 2018 · 2018
Cited alongside, same era.
Marian: Cost-effective high-quality neural machine translation in C++
Marcin Junczys-Dowmunt, Kenneth Heafield, Hieu Hoang, Roman Grundkiewicz, and Anthony Aue. 2018 · 2018
Cited alongside, same era.
Can neural machine translation be improved with user feedback?
Julia Kreutzer, Shahram Khadivi, Evgeny Matusov, and Stefan Riezler. 2018 · 2018
Cited alongside, same era.
Neural transition-based string transduction for limited-resource setting in morphology
Peter Makarov and Simon Clematide. 2018 · 2018
Cited alongside, same era.
Junjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, and Melvin Johnson. 2020 · 2020
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From zero to hero: On the limitations of zero-shot language transfer with multilingual Transformers
Anne Lauscher, Vinit Ravishankar, Ivan Vulić, and Goran Glavaš. 2020 · 2020
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Multilingual graphemic hybrid ASR with massive data augmentation
Chunxi Liu, Qiaochu Zhang, Xiaohui Zhang, Kritika Singh, Yatharth Saraf, and Geoffrey Zweig. 2020 · 2020
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Improving the naturalness and diversity of referring expression generation models using minimum risk training
Nikolaos Panagiaris, Emma Hart, and Dimitra Gkatzia. 2020 · 2020
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XCOPA: A multilingual dataset for causal commonsense reasoning
Edoardo Maria Ponti, Goran Glavaš, Olga Majewska, Qianchu Liu, Ivan Vulić, and Anna Korhonen. 2020 · 2020
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Using context in neural machine translation training objectives
Danielle Saunders, Felix Stahlberg, and Bill Byrne. 2020 · 2020
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Evaluating the cross-lingual effectiveness of massively multilingual neural machine translation
Aditya Siddhant, Melvin Johnson, Henry Tsai, Naveen Ari, Jason Riesa, Ankur Bapna, Orhan Firat, and Karthik Raman. 2020 · 2020
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OPUS-MT – building open translation services for the world
Jörg Tiedemann and Santhosh Thottingal. 2020 · 2020
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On exposure bias, hallucination and domain shift in neural machine translation
Chaojun Wang and Rico Sennrich. 2020 · 2020
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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 · 2020
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Should we stop training more monolingual models, and simply use machine translation instead?
Tim Isbister, Fredrik Carlsson, and Magnus Sahlgren. 2021 · 2021
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Parameter Space Factorization for Zero-Shot Learning across Tasks and Languages
Edoardo M. Ponti, Ivan Vulić, Ryan Cotterell, Marinela Parovic, Roi Reichart, and Anna Korhonen. 2021 · 2021
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XTREME-R: Towards more challenging and nuanced multilingual evaluation
Sebastian Ruder, Noah Constant, Jan Botha, Aditya Siddhant, Orhan Firat, Jinlan Fu, Pengfei Liu, Junjie Hu, Graham Neubig, and Melvin Johnson. 2021 · 2021
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