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Neural machine translation (NMT) has arguably achieved human level parity when trained and evaluated at the sentence-level.
Revisiting self-training for neural sequence generation
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Effective self-training for parsing
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Using monolingual source-language data to improve mt performance
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Self-training for enhancement and domain adaptation of statistical parsers trained on small datasets
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Self-training pcfg grammars with latent annotations across languages
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Statistical language models based on neural networks
Tomas Mikolov. 2012 · 2012
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Generating sequences with recurrent neural networks
Alex Graves. 2013 · 2013
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Recurrent continuous translation models
Nal Kalchbrenner and Phil Blunsom. 2013 · 2013
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Pseudo-label : The simple and efficient semi-supervised learning method for deep neural networks
Dong-Hyun Lee. 2013 · 2013
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Contextual handling in neural machine translation: Look behind, ahead and on both sides
Ruchit Agrawal, Marco Turchi, and Matteo Negri. 2018 · 2018
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Understanding back-translation at scale
Sergey Edunov, Myle Ott, Michael Auli, and David Grangier. 2018 · 2018
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Achieving human parity on automatic chinese to english news translation
Hany Hassan, Anthony Aue, Chang Chen, Vishal Chowdhary, Jonathan Clark, Christian Federmann, Xuedong Huang, Marcin Junczys-Dowmunt, William Lewis, Mu Li, Shujie Liu, Tie-Yan Liu, Renqian Luo, Arul Menezes, Tao Qin, Frank Seide, Xu Tan, Fei Tian, Lijun Wu, Shuangzhi Wu, Yingce Xia, Dongdong Zhang, Zhirui Zhang, and Ming Zhou. 2018 · 2018
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Dynamic evaluation of neural sequence models
Ben Krause, Emmanuel Kahembwe, Iain Murray, and Steve Renals. 2018 · 2018
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Document context neural machine translation with memory networks
Sameen Maruf and Gholamreza Haffari. 2018 · 2018
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Diederik P Kingma and Jimmy Ba. 2014 · 2014
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Using fast weights to attend to the recent past
Jimmy Ba, Geoffrey E. Hinton, Volodymyr Mnih, Joel Z. Leibo, and Catalin Ionescu. 2016 · 2016
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Exploiting source-side monolingual data in neural machine translation
Jiajun Zhang and Chengqing Zong. 2016 · 2016
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Does neural machine translation benefit from larger context?
Sebastien Jean, Stanislas Lauly, Orhan Firat, and Kyunghyun Cho. 2017 · 2017
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Modeling coherence for neural machine translation with dynamic and topic caches
Shaohui Kuang, Deyi Xiong, Weihua Luo, and Guodong Zhou. 2017 · 2017
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Document-level neural machine translation with hierarchical attention networks
Lesly Miculicich, Dhananjay Ram, Nikolaos Pappas, and James Henderson. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Why the Time Is Ripe for Discourse in Machine Translation
Rico Sennrich. 2018 · 2018
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Tensor2tensor for neural machine translation
Ashish Vaswani, Samy Bengio, Eugene Brevdo, Francois Chollet, Aidan N. Gomez, Stephan Gouws, Llion Jones, Łukasz Kaiser, Nal Kalchbrenner, Niki Parmar, Ryan Sepassi, Noam Shazeer, and Jakob Uszkoreit. 2018 · 2018
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Modeling coherence for discourse neural machine translation
Hao Xiong, Zhongjun He, Hua Wu, and Haifeng Wang. 2018 · 2018
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Improving the transformer translation model with document-level context
Jiacheng Zhang, Huanbo Luan, Maosong Sun, Feifei Zhai, Jingfang Xu, Min Zhang, and Yang Liu. 2018 · 2018
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Findings of the 2019 conference on machine translation (WMT19)
Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Philipp Koehn, Shervin Malmasi, Christof Monz, Mathias Müller, Santanu Pal, Matt Post, and Marcos Zampieri. 2019 · 2019
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Microsoft translator at wmt 2019: Towards large-scale document-level neural machine translation
Marcin Junczys-Dowmunt. 2019 · 2019
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Proceedings of the Fourth Workshop on Discourse in Machine Translation (DiscoMT 2019)
Andrei Popescu-Belis, Sharid Loáiciga, Christian Hardmeier, and Deyi Xiong. 2019 · 2019
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Microsoft research asia’s systems for WMT19
Yingce Xia, Xu Tan, Fei Tian, Fei Gao, Di He, Weicong Chen, Yang Fan, Linyuan Gong, Yichong Leng, Renqian Luo, Yiren Wang, Lijun Wu, Jinhua Zhu, Tao Qin, and Tie-Yan Liu. 2019 · 2019
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Simple and effective noisy channel modeling for neural machine translation
Kyra Yee, Nathan Ng, Yann N. Dauphin, and Michael Auli. 2019 · 2019
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