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Translating characters instead of words or word-fragments has the potential to simplify the processing pipeline for neural machine translation (NMT), and improve results by eliminating hyper-parameters and manual feature engineering.
Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville. 2013 · 2013
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Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Lei Ba. 2014 · 2014
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Character-based neural machine translation
Wang Ling, Isabel Trancoso, Chris Dyer, and Alan W Black. 2015 · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton. 2016 · 2016
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Quasi-recurrent neural networks
James Bradbury, Stephen Merity, Caiming Xiong, and Richard Socher. 2016 · 2016
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Listen, attend and spell: A neural network for large vocabulary conversational speech recognition
William Chan, Navdeep Jaitly, Quoc Le, and Oriol Vinyals. 2016 · 2016
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Character-based neural machine translation
Marta R. Costa-jussà and José A. R. Fonollosa. 2016 · 2016
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Achieving open vocabulary neural machine translation with hybrid word-character models
Minh-Thang Luong and Christopher D. Manning. 2016 · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Modeling coverage for neural machine translation
Zhaopeng Tu, Zhengdong Lu, Yang Liu, Xiaohua Liu, and Hang Li. 2016 · 2016
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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 Kazawaand 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
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Hierarchical multiscale recurrent neural networks
Junyoung Chung, Sungjin Ahn, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
Plan, attend, generate: Character-level neural machine translation with planning
How Grammatical is Character-level Neural Machine Translation? Assessing MT Quality with Contrastive Translation Pairs
Rico Sennrich. 2017 · 2017
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The best of both worlds: Combining recent advances in neural machine translation
Mia Xu Chen, Orhan Firat, Ankur Bapna, Melvin Johnson, Wolfgang Macherey, George Foster, Llion Jones, Niki Parmar, Mike Schuster, Zhifeng Chen, Yonghui Wu, and Macduff Hughes. 2018 · 2018
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Fast decoding in sequence models using discrete latent variables
Łukasz Kaiser, Aurko Roy, Ashish Vaswani, Niki Parmar, Samy Bengio, Jakob Uszkoreit, and Noam Shazeer. 2018 · 2018
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Focused hierarchical RNNs for conditional sequence processing
Nan Rosemary Ke, Konrad Zolna, Alessandro Sordoni, Zhouhan Lin, Adam Trischler, Yoshua Bengio, Joelle Pineau, Laurent Charlin, and Chris Pal. 2018 · 2018
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Subword regularization: Improving neural network translation models with multiple subword candidates
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Caglar Gulcehre, Francis Dutil, Adam Trischler, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
Google’s multilingual neural machine translation system: Enabling zero-shot translation
Melvin Johnson, Mike Schuster, Quoc Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernand a Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2017 · 2017
Cited alongside, same era.
Fully character-level neural machine translation without explicit segmentation
Jason Lee, Kyunghyun Cho, and Thomas Hofmann. 2017 · 2017
Cited alongside, same era.
Online and linear-time attention by enforcing monotonic alignments
Colin Raffel, Minh-Thang Luong, Peter J. Liu, Ron J. Weiss, and Douglas Eck. 2017 · 2017
Cited alongside, same era.
Taku Kudo. 2018 · 2018
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Revisiting the hierarchical multiscale LSTM
Ákos Kádár, Marc-Alexandre Côté, Grzegorz Chrupała, and Afra Alishahi. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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