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Attentional sequence-to-sequence models have become the new standard for machine translation, but one challenge of such models is a significant increase in training and decoding cost compared to phrase-based systems.
The mathematics of statistical machine translation: Parameter estimation
Peter F Brown, Vincent J Della Pietra, Stephen A Della Pietra, and Robert L Mercer. 1993 · 1993
Earlier work this paper cites.
Faster beam-search decoding for phrasal statistical machine translation
Chris Quirk and Robert Moore. 2007 · 2007
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Fast and robust neural network joint models for statistical machine translation
Jacob Devlin, Rabih Zbib, Zhongqiang Huang, Thomas Lamar, Richard M Schwartz, and John Makhoul. 2014 · 2014
Earlier work this paper cites.
Edinburgh’s phrase-based machine translation systems for wmt-14
Nadir Durrani, Barry Haddow, Philipp Koehn, and Kenneth Heafield. 2014 · 2014
Earlier work this paper cites.
http://www-lium.univ-lemans.fr/schwenk/cslm_joint_paper
Holger Schwenk. 2014 · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
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On using very large target vocabulary for neural machine translation
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Cited alongside, same era.
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Jonas Gehring, Michael Auli, David Grangier, and Yann N Dauphin. 2016 · 2016
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Neural machine translation in linear time
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Later among the works it cites.
Sequence-level knowledge distillation
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Later among the works it cites.
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, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2016 · 2016
Later among the works it cites.
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Deep compression: Compressing deep neural network with pruning, trained quantization and huffman coding
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Jie Zhou, Ying Cao, Xuguang Wang, Peng Li, and Wei Xu. 2016 · 2016
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