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Domain adaptation is an important challenge for neural machine translation.
Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 1901
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Alleviating the inequality of attention heads for neural machine translation
Zewei Sun, Shujian Huang, Xinyu Dai, and Jiajun Chen. 2020a · 2009
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Statistical Machine Translation
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Few-shot text generation with pattern-exploiting training
Timo Schick and Hinrich Schütze. 2020 · 2012
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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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Six challenges for neural machine translation
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Attention is all you need
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Encoding gated translation memory into neural machine translation
Qian Cao and Deyi Xiong. 2018 · 2018
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A survey of domain adaptation for neural machine translation
Chenhui Chu and Rui Wang. 2018 · 2018
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Deep contextualized word representations
Matthew Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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Simple, scalable adaptation for neural machine translation
Ankur Bapna and Orhan Firat. 2019 · 2019
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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
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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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Neural machine translation with monolingual translation memory
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Exploiting cloze-questions for few-shot text classification and natural language inference
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Automatically identifying words that can serve as labels for few-shot text classification
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What makes good in-context examples for gpt-3?
Jiachang Liu, Dinghan Shen, Yizhe Zhang, Bill Dolan, Lawrence Carin, and Weizhu Chen. 2021a
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Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2021b
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Timo Schick and Hinrich Schütze. 2021 · 2021
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Multilingual translation via grafting pre-trained language models
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Using natural language prompts for machine translation
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Rethinking document-level neural machine translation
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