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Beam search is widely used in neural machine translation, and usually improves translation quality compared to greedy search.
Conditional random fields: Probabilistic models for segmenting and labeling sequence data
John Lafferty, Andrew McCallum, and Fernando Pereira. 2001 · 2001
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Bleu: a method for automatic evaluation of machine translation
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Recurrent continuous translation models
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Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Rico Sennrich, Barry Haddow, and Alexandra Birch. 2015 · 2015
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Xing Shi, Kevin Knight, and Deniz Yuret. 2016 · 2016
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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
When to finish? optimal beam search for neural text generation (modulo beam size)
Liang Huang, Kai Zhao, and Mingbo Ma. 2017 · 2017
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OpenNMT: Open-Source Toolkit for Neural Machine Translation
G. Klein, Y. Kim, Y. Deng, J. Senellart, and A. M. Rush. 2017 · 2017
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Six challenges for neural machine translation
Philipp Koehn and Rebecca Knowles. 2017 · 2017
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Neural machine translation with reconstruction
Zhaopeng Tu, Yang Liu, Lifeng Shang, Xiaohua Liu, and Hang Li. 2017 · 2017
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Correcting length bias in neural machine translation
Kenton Murray and David Chiang. 2018 · 2018
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