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Pre-trained cross-lingual encoders such as mBERT (Devlin et al., 2019) and XLMR (Conneau et al., 2020) have proven to be impressively effective at enabling transfer-learning of NLP systems from high-resource languages to low-resource 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
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The mathematics of statistical machine translation: Parameter estimation
Peter F. Brown, Stephen A. Della Pietra, Vincent J. Della Pietra, and Robert L. Mercer. 1993 · 1993
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Improving vector space word representations using multilingual correlation
Manaal Faruqui and Chris Dyer. 2014 · 2014
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Normalized word embedding and orthogonal transform for bilingual word translation
Chao Xing, Dong Wang, Chao Liu, and Yiye Lin. 2015 · 2015
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Incorporating structural alignment biases into an attentional neural translation model
Trevor Cohn, Cong Duy Vu Hoang, Ekaterina Vymolova, Kaisheng Yao, Chris Dyer, and Gholamreza Haffari. 2016 · 2016
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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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Neural network-based word alignment through score aggregation
Joël Legrand, Michael Auli, and Ronan Collobert. 2016 · 2016
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What does attention in neural machine translation pay attention to?
Hamidreza Ghader and Christof Monz. 2017 · 2017
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Learned in translation: Contextualized word vectors
Bryan McCann, James Bradbury, Caiming Xiong, and Richard Socher. 2017 · 2017
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On the alignment problem in multi-head attention-based neural machine translation
Tamer Alkhouli, Gabriel Bretschner, and Hermann Ney. 2018 · 2018
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XNLI: Evaluating cross-lingual sentence representations
Alexis Conneau, Ruty Rinott, Guillaume Lample, Adina Williams, Samuel Bowman, Holger Schwenk, and Veselin Stoyanov. 2018 · 2018
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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.
Universal dependencies 2.2
Joakim Nivre, Mitchell Abrams, Željko Agić, Lars Ahrenberg, Lene Antonsen, Maria Jesus Aranzabe, Gashaw Arutie, Masayuki Asahara, Luma Ateyah, Mohammed Attia, et al. 2018 · 2018
Cited alongside, same era.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
Cited alongside, same era.
Massively multilingual sentence embeddings for zero-shot cross-lingual transfer and beyond
Mikel Artetxe and Holger Schwenk. 2019 · 2019
Cited alongside, same era.
Cross-lingual language model pretraining
Alexis Conneau and Guillaume Lample. 2019 · 2019
Cited alongside, same era.
Cross-lingual BERT transformation for zero-shot dependency parsing
Yuxuan Wang, Wanxiang Che, Jiang Guo, Yijia Liu, and Ting Liu. 2019 · 2019
Later among the works it cites.
Simple and effective paraphrastic similarity from parallel translations
John Wieting, Kevin Gimpel, Graham Neubig, and Taylor Berg-Kirkpatrick. 2019 · 2019
Later among the works it cites.
Beto, bentz, becas: The surprising cross-lingual effectiveness of BERT
Shijie Wu and Mark Dredze. 2019 · 2019
Later among the works it cites.
PAWS-X: A cross-lingual adversarial dataset for paraphrase identification
Yinfei Yang, Yuan Zhang, Chris Tar, and Jason Baldridge. 2019b · 2019
Later among the works it cites.
PAWS: Paraphrase adversaries from word scrambling
Yuan Zhang, Jason Baldridge, and Luheng He. 2019 · 2019
Later among the works it cites.
On the cross-lingual transferability of monolingual representations
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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.
Unicoder: A universal language encoder by pre-training with multiple cross-lingual tasks
Haoyang Huang, Yaobo Liang, Nan Duan, Ming Gong, Linjun Shou, Daxin Jiang, and Ming Zhou. 2019 · 2019
Cited alongside, same era.
On the word alignment from neural machine translation
Xintong Li, Guanlin Li, Lemao Liu, Max Meng, and Shuming Shi. 2019 · 2019
Cited alongside, same era.
Choosing transfer languages for cross-lingual learning
Yu-Hsiang Lin, Chian-Yu Chen, Jean Lee, Zirui Li, Yuyan Zhang, Mengzhou Xia, Shruti Rijhwani, Junxian He, Zhisong Zhang, Xuezhe Ma, Antonios Anastasopoulos, Patrick Littell, and Graham Neubig. 2019 · 2019
Cited alongside, same era.
How multilingual is multilingual BERT?
Telmo Pires, Eva Schlinger, and Dan Garrette. 2019 · 2019
Cited alongside, same era.
Cross-lingual alignment of contextual word embeddings, with applications to zero-shot dependency parsing
Tal Schuster, Ori Ram, Regina Barzilay, and Amir Globerson. 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. 2020a
Cited in the paper.
Mikel Artetxe, Sebastian Ruder, and Dani Yogatama. 2020 · 2020
Closest in time.
Multilingual alignment of contextual word representations
Steven Cao, Nikita Kitaev, and Dan Klein. 2020 · 2020
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XTREME: A massively multilingual multi-task benchmark for evaluating cross-lingual generalisation
Junjie Hu, Sebastian Ruder, Aditya Siddhant, Graham Neubig, Orhan Firat, and Melvin Johnson. 2020 · 2020
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Cross-lingual ability of multilingual bert: An empirical study
Karthikeyan K, Zihan Wang, Stephen Mayhew, and Dan Roth. 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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Cross-lingual alignment vs joint training: A comparative study and a simple unified framework
Zirui Wang, Jiateng Xie, Ruochen Xu, Yiming Yang, Graham Neubig, and Jaime G. Carbonell. 2020 · 2020
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