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Despite the progress in machine translation quality estimation and evaluation in the last years, decoding in neural machine translation (NMT) is mostly oblivious to this and centers around finding the most probable translation according to the model (MAP decoding), approximated with beam search.
Minimum bayes-risk word alignments of bilingual texts
Shankar Kumar and William Byrne. 2002 · 2002
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Minimum error rate training in statistical machine translation
Franz Josef Och. 2003 · 2003
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Minimum Bayes-risk decoding for statistical machine translation
Shankar Kumar and William Byrne. 2004 · 2004
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Discriminative reranking for machine translation
Libin Shen, Anoop Sarkar, and Franz Josef Och. 2004 · 2004
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Minimum risk annealing for training log-linear models
David A. Smith and Jason Eisner. 2006 · 2006
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Beyond log-linear models: Boosted minimum error rate training for n-best re-ranking
Kevin Duh and Katrin Kirchhoff. 2008 · 2008
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The meteor metric for automatic evaluation of machine translation
Alon Lavie and Michael J. Denkowski. 2009 · 2009
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WIT3: Web inventory of transcribed and translated talks
Mauro Cettolo, Christian Girardi, and Marcello Federico. 2012 · 2012
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Sequence transduction with recurrent neural networks
Alex Graves. 2012 · 2012
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Continuous measurement scales in human evaluation of machine translation
Yvette Graham, Timothy Baldwin, Alistair Moffat, and Justin Zobel. 2013 · 2013
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Travatar: A forest-to-string machine translation engine based on tree transducers
Graham Neubig. 2013 · 2013
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Multidimensional quality metrics (MQM): A framework for declaring and describing translation quality metrics
Arle Lommel, Aljoscha Burchardt, and Hans Uszkoreit. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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chrF: character n-gram F-score for automatic MT evaluation
Maja Popović. 2015 · 2015
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Minimum risk training for neural machine translation
Shiqi Shen, Yong Cheng, Zhongjun He, Wei He, Hua Wu, Maosong Sun, and Yang Liu. 2016 · 2016
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Rethinking the inception architecture for computer vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jon Shlens, and Zbigniew Wojna. 2016 · 2016
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Six challenges for neural machine translation
Philipp Koehn and Rebecca Knowles. 2017 · 2017
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Later-stage minimum bayes-risk decoding for neural machine translation
Raphael Shu and Hideki Nakayama. 2017 · 2017
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Neural machine translation by minimising the Bayes-risk with respect to syntactic translation lattices
Felix Stahlberg, Adrià de Gispert, Eva Hasler, and Bill Byrne. 2017 · 2017
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The neural noisy channel
Lei Yu, Phil Blunsom, Chris Dyer, Edward Grefenstette, and Tomás Kociský. 2017 · 2017
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Classical structured prediction losses for sequence to sequence learning
Sergey Edunov, Myle Ott, Michael Auli, David Grangier, and Marc’Aurelio Ranzato. 2018 · 2018
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
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SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
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Correcting length bias in neural machine translation
Kenton Murray and David Chiang. 2018 · 2018
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Analyzing uncertainty in neural machine translation
Myle Ott, Michael Auli, David Grangier, and Marc’Aurelio Ranzato. 2018 · 2018
TransQuest: Translation quality estimation with cross-lingual transformers
Tharindu Ranasinghe, Constantin Orasan, and Ruslan Mitkov. 2020 · 2020
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COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020a · 2020
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BLEURT: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
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Findings of the WMT 2020 shared task on quality estimation
Lucia Specia, Frédéric Blain, Marina Fomicheva, Erick Fonseca, Vishrav Chaudhary, Francisco Guzmán, and André F. T. Martins. 2020 · 2020
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On exposure bias, hallucination and domain shift in neural machine translation
Chaojun Wang and Rico Sennrich. 2020 · 2020
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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Cited alongside, same era.
A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
Cited alongside, same era.
Breaking the beam search curse: A study of (re-)scoring methods and stopping criteria for neural machine translation
Yilin Yang, Liang Huang, and Mingbo Ma. 2018 · 2018
Cited alongside, same era.
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 · 2019
Cited alongside, same era.
OpenKiwi: An open source framework for quality estimation
Fabio Kepler, Jonay Trénous, Marcos Treviso, Miguel Vera, and André F. T. Martins. 2019 · 2019
Cited alongside, same era.
When does label smoothing help?
Rafael Müller, Simon Kornblith, and Geoffrey E Hinton. 2019 · 2019
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Facebook FAIR’s WMT19 news translation task submission
Nathan Ng, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, and Sergey Edunov. 2019 · 2019
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Energy-based reranking: Improving neural machine translation using energy-based models
Sumanta Bhattacharyya, Amirmohammad Rooshenas, Subhajit Naskar, Simeng Sun, Mohit Iyyer, and Andrew McCallum. 2021 · 2021
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Rethinking embedding coupling in pre-trained language models
Hyung Won Chung, Thibault Fevry, Henry Tsai, Melvin Johnson, and Sebastian Ruder. 2021 · 2021
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Sampling-based minimum bayes risk decoding for neural machine translation
Bryan Eikema and Wilker Aziz. 2021 · 2021
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Revisiting the weaknesses of reinforcement learning for neural machine translation
Samuel Kiegeland and Julia Kreutzer. 2021 · 2021
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To ship or not to ship: An extensive evaluation of automatic metrics for machine translation
Tom Kocmi, Christian Federmann, Roman Grundkiewicz, Marcin Junczys-Dowmunt, Hitokazu Matsushita, and Arul Menezes. 2021 · 2021
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Machine translation decoding beyond beam search
Rémi Leblond, Jean-Baptiste Alayrac, Laurent Sifre, Miruna Pislar, Lespiau Jean-Baptiste, Ioannis Antonoglou, Karen Simonyan, and Oriol Vinyals. 2021 · 2021
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Discriminative reranking for neural machine translation
Ann Lee, Michael Auli, and Marc’Aurelio Ranzato. 2021 · 2021
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Understanding the properties of minimum Bayes risk decoding in neural machine translation
Mathias Müller and Rico Sennrich. 2021 · 2021
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Learning compact metrics for MT
Amy Pu, Hyung Won Chung, Ankur Parikh, Sebastian Gehrmann, and Thibault Sellam. 2021 · 2021
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Are references really needed? unbabel-IST 2021 submission for the metrics shared task
Ricardo Rei, Ana C Farinha, Chrysoula Zerva, Daan van Stigt, Craig Stewart, Pedro Ramos, Taisiya Glushkova, André F. T. Martins, and Alon Lavie. 2021 · 2021
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What do you get when you cross beam search with nucleus sampling?
Uri Shaham and Omer Levy. 2021 · 2021
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Findings of the WMT 2021 shared task on quality estimation
Lucia Specia, Frédéric Blain, Marina Fomicheva, Chrysoula Zerva, Zhenhao Li, Vishrav Chaudhary, and André F. T. Martins. 2021 · 2021
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IST-unbabel 2021 submission for the quality estimation shared task
Chrysoula Zerva, Daan van Stigt, Ricardo Rei, Ana C Farinha, Pedro Ramos, José G. C. de Souza, Taisiya Glushkova, Miguel Vera, Fabio Kepler, and André F. T. Martins. 2021 · 2021
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Identifying weaknesses in machine translation metrics through minimum bayes risk decoding: A case study for comet
Chantal Amrhein and Rico Sennrich. 2022 · 2022
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