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Simultaneous machine translation models start generating a target sequence before they have encoded or read the source sequence.
Don’t until the final verb wait: Reinforcement learning for simultaneous machine translation
Alvin Grissom II, He He, Jordan Boyd-Graber, John Morgan, and Hal Daumé III · 2014
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Stanford neural machine translation systems for spoken language domains
Minh-Thang Luong and Christopher D Manning · 2015
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Effective approaches to attention-based neural machine translation
Minh-Thang Luong, Hieu Pham, and Christopher D Manning · 2015
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The iwslt 2016 evaluation campaign
Mauro Cettolo, Niehues Jan, Stüker Sebastian, Luisa Bentivogli, Roldano Cattoni, and Marcello Federico · 2016
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Can neural machine translation do simultaneous translation?
Kyunghyun Cho and Masha Esipova · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch · 2016
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Learning to translate in real-time with neural machine translation
Jiatao Gu, Graham Neubig, Kyunghyun Cho, and Victor OK Li · 2017
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Online and linear-time attention by enforcing monotonic alignments
Colin Raffel, Minh-Thang Luong, Peter J Liu, Ron J Weiss, and Douglas Eck · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
Cited alongside, same era.
Prediction improves simultaneous neural machine translation
Ashkan Alinejad, Maryam Siahbani, and Anoop Sarkar · 2018
Cited alongside, same era.
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, Mike Schuster, Noam Shazeer, Niki Parmar, et al · 2018
Cited alongside, same era.
Monotonic chunkwise attention
Chung-Cheng Chiu and Colin Raffel · 2018
Cited alongside, same era.
A call for clarity in reporting BLEU scores
Matt Post · 2018
Monotonic infinite lookback attention for simultaneous machine translation
Naveen Arivazhagan, Colin Cherry, Wolfgang Macherey, Chung-Cheng Chiu, Semih Yavuz, Ruoming Pang, Wei Li, and Colin Raffel · 2019
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Findings of the 2019 conference on machine translation (WMT19)
Loïc Barrault, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Philipp Koehn, Shervin Malmasi, Christof Monz, Mathias Müller, Santanu Pal, Matt Post, and Marcos Zampieri · 2019
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STACL: Simultaneous translation with implicit anticipation and controllable latency using prefix-to-prefix framework
Mingbo Ma, Liang Huang, Hao Xiong, Renjie Zheng, Kaibo Liu, Baigong Zheng, Chuanqiang Zhang, Zhongjun He, Hairong Liu, Xing Li, Hua Wu, and Haifeng Wang · 2019
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fairseq: A fast, extensible toolkit for sequence modeling
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli · 2019
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Moses: Open source toolkit for statistical machine translation
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondřej Bojar, Alexandra Constantin, and Evan Herbst · 2045
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Cited alongside, same era.
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Incremental decoding and training methods for simultaneous translation in neural machine translation
Fahim Dalvi, Nadir Durrani, Hassan Sajjad, and Stephan Vogel · 2079
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