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Statistical significance tests for machine translation evaluation
Philipp Koehn. 2004 · 2004
Earlier work this paper cites.
Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics
Chin-Yew Lin and Franz Josef Och. 2004 · 2004
Earlier work this paper cites.
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
Tijmen Tieleman and Geoffrey Hinton. 2012 · 2012
Earlier work this paper cites.
Adadelta: an adaptive learning rate method
Original
Matthew D Zeiler. 2012 · 2012
Earlier work this paper cites.
Recurrent continuous translation models
Nal Kalchbrenner and Phil Blunsom. 2013 · 2013
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Original
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
Original
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Deterministic policy gradient algorithms
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, and Martin Riedmiller. 2014 · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Earlier work this paper cites.
Multi-task learning for multiple language translation
Daxiang Dong, Hua Wu, Wei He, Dianhai Yu, and Haifeng Wang. 2015 · 2015
Earlier work this paper cites.
Learning continuous control policies by stochastic value gradients
Nicolas Heess, Gregory Wayne, David Silver, Tim Lillicrap, Tom Erez, and Yuval Tassa. 2015 · 2015
Earlier work this paper cites.
Continuous control with deep reinforcement learning
Original
Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra. 2015 · 2015
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Jiatao Gu, Graham Neubig, Kyunghyun Cho, and Victor OK Li. 2016 · 2016
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Thanh-Le Ha, Jan Niehues, and Alexander Waibel. 2016 · 2016
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Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan, Aaron van den Oord, Alex Graves, and Koray Kavukcuoglu. 2016 · 2016
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Fully character-level neural machine translation without explicit segmentation
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A simple, fast diverse decoding algorithm for neural generation

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2017

Trainable Greedy Decoding for Neural Machine Translation

Gu, Jiatao, Cho, Kyunghyun, Li, Victor O. K.

Understand

Recent research in neural machine translation has largely focused on two aspects; neural network architectures and end-to-end learning algorithms.

The problem of decoding, however, has received relatively little attention from the research community.
In this paper, we solely focus on the problem of decoding given a trained neural machine translation model.
Instead of trying to build a new decoding algorithm for any specific decoding objective, we propose the idea of trainable decoding algorithm in which we train a decoding algorithm to find a translation that maximizes an arbitrary decoding objective.

Built on

Statistical significance tests for machine translation evaluation
Philipp Koehn. 2004 · 2004
Earlier work this paper cites.
Automatic evaluation of machine translation quality using longest common subsequence and skip-bigram statistics
Chin-Yew Lin and Franz Josef Och. 2004 · 2004
Earlier work this paper cites.
Lecture 6.5-rmsprop: Divide the gradient by a running average of its recent magnitude
Tijmen Tieleman and Geoffrey Hinton. 2012 · 2012
Earlier work this paper cites.
Adadelta: an adaptive learning rate method
Original
Matthew D Zeiler. 2012 · 2012
Earlier work this paper cites.
Recurrent continuous translation models
Nal Kalchbrenner and Phil Blunsom. 2013 · 2013
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Original
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Learning phrase representations using rnn encoder-decoder for statistical machine translation
Original
Kyunghyun Cho, Bart Van Merriënboer, Caglar Gulcehre, Dzmitry Bahdanau, Fethi Bougares, Holger Schwenk, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Deterministic policy gradient algorithms
David Silver, Guy Lever, Nicolas Heess, Thomas Degris, Daan Wierstra, and Martin Riedmiller. 2014 · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Earlier work this paper cites.
Multi-task learning for multiple language translation
Daxiang Dong, Hua Wu, Wei He, Dianhai Yu, and Haifeng Wang. 2015 · 2015
Earlier work this paper cites.
Learning continuous control policies by stochastic value gradients
Nicolas Heess, Gregory Wayne, David Silver, Tim Lillicrap, Tom Erez, and Yuval Tassa. 2015 · 2015
Earlier work this paper cites.
Continuous control with deep reinforcement learning
Original
Timothy P Lillicrap, Jonathan J Hunt, Alexander Pritzel, Nicolas Heess, Tom Erez, Yuval Tassa, David Silver, and Daan Wierstra. 2015 · 2015
Earlier work this paper cites.

Similar

Character-based neural machine translation
Original
Wang Ling, Isabel Trancoso, Chris Dyer, and Alan W Black. 2015 · 2015
Cited alongside, same era.
Sequence level training with recurrent neural networks
Original
Marc’Aurelio Ranzato, Sumit Chopra, Michael Auli, and Wojciech Zaremba. 2015 · 2015
Cited alongside, same era.
Neural machine translation of rare words with subword units
Original
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2015 · 2015
Cited alongside, same era.
Minimum risk training for neural machine translation
Original
Shiqi Shen, Yong Cheng, Zhongjun He, Wei He, Hua Wu, Maosong Sun, and Yang Liu. 2015 · 2015
Cited alongside, same era.
An actor-critic algorithm for sequence prediction

Then

Learning to translate in real-time with neural machine translation
Original
Jiatao Gu, Graham Neubig, Kyunghyun Cho, and Victor OK Li. 2016 · 2016
Later among the works it cites.
Toward multilingual neural machine translation with universal encoder and decoder
Original
Thanh-Le Ha, Jan Niehues, and Alexander Waibel. 2016 · 2016
Later among the works it cites.
Neural machine translation in linear time
Original
Nal Kalchbrenner, Lasse Espeholt, Karen Simonyan, Aaron van den Oord, Alex Graves, and Koray Kavukcuoglu. 2016 · 2016
Later among the works it cites.
Fully character-level neural machine translation without explicit segmentation
Original
Jason Lee, Kyunghyun Cho, and Thomas Hofmann. 2016 · 2016
Later among the works it cites.
A simple, fast diverse decoding algorithm for neural generation

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Original

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Marta R Costa-Jussa and José AR Fonollosa. 2016 · 2016

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Josep Crego, Jungi Kim, Guillaume Klein, Anabel Rebollo, Kathy Yang, Jean Senellart, Egor Akhanov, Patrice Brunelle, Aurelien Coquard, Yongchao Deng, et al. 2016 · 2016

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A convolutional encoder model for neural machine translation

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Jonas Gehring, Michael Auli, David Grangier, and Yann N Dauphin. 2016 · 2016

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Multi-way, multilingual neural machine translation with a shared attention mechanism

Orhan Firat, Kyunghyun Cho, and Yoshua Bengio. 2016a

Cited in the paper.

Original

Jiwei Li, Will Monroe, and Dan Jurafsky. 2016 · 2016