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Generating multiple translation candidates would enable users to choose the one that satisfies their needs.
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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The Kyoto free translation task
Graham Neubig. 2011 · 2011
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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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Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
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A systematic exploration of diversity in machine translation
Kevin Gimpel, Dhruv Batra, Chris Dyer, and Gregory Shakhnarovich. 2013 · 2013
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A systematic comparison of smoothing techniques for sentence-level BLEU
Boxing Chen and Colin Cherry. 2014 · 2014
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Noisy parallel approximate decoding for conditional recurrent language model
Kyunghyun Cho. 2016 · 2016
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Mutual information and diverse decoding improve neural machine translation
Jiwei Li and Dan Jurafsky. 2016 · 2016
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Counter-fitting word vectors to linguistic constraints
Nikola Mrkšić, Diarmuid Ó Séaghdha, Blaise Thomson, Milica Gašić, Lina M. Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
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ASPEC: Asian scientific paper excerpt corpus
Toshiaki Nakazawa, Manabu Yaguchi, Kiyotaka Uchimoto, Masao Utiyama, Eiichiro Sumita, Sadao Kurohashi, and Hitoshi Isahara. 2016 · 2016
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Beam search strategies for neural machine translation
Markus Freitag and Yaser Al-Onaizan. 2017 · 2017
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Six challenges for neural machine translation
Philipp Koehn and Rebecca Knowles. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Diverse beam search for improved description of complex scenes
Ashwin Vijayakumar, Michael Cogswell, Ramprasaath Selvaraju, Qing Sun, Stefan Lee, David Crandall, and Dhruv Batra. 2018 · 2018
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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 · 2019
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BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
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Comparison of diverse decoding methods from conditional language models
Daphne Ippolito, Reno Kriz, João Sedoc, Maria Kustikova, and Chris Callison-Burch. 2019 · 2019
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Billion-scale similarity search with GPUs
Jeff Johnson, Matthijs Douze, and Hervé Jégou. 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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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
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Findings of the 2021 conference on machine translation (WMT21)
Farhad Akhbardeh, Arkady Arkhangorodsky, Magdalena Biesialska, Ondřej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-jussa, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, and Marcos Zampieri. 2021 · 2021
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Learning kernel-smoothed machine translation with retrieved examples
Qingnan Jiang, Mingxuan Wang, Jun Cao, Shanbo Cheng, Shujian Huang, and Lei Li. 2021 · 2021
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Nearest neighbor machine translation
Urvashi Khandelwal, Angela Fan, Dan Jurafsky, Luke Zettlemoyer, and Mike Lewis. 2021 · 2021
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Mixup decoding for diverse machine translation
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fairseq: A fast, extensible toolkit for sequence modeling
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Designing the business conversation corpus
Matīss Rikters, Ryokan Ri, Tong Li, and Toshiaki Nakazawa. 2019 · 2019
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Generating diverse translations with sentence codes
Raphael Shu, Hideki Nakayama, and Kyunghyun Cho. 2019 · 2019
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Bridging the gap between training and inference for neural machine translation
Wen Zhang, Yang Feng, Fandong Meng, Di You, and Qun Liu. 2019 · 2019
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Unsupervised domain clusters in pretrained language models
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The curious case of neural text degeneration
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COMET: A neural framework for MT evaluation
Ricardo Rei, Craig Stewart, Ana C Farinha, and Alon Lavie. 2020 · 2020
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Trading off diversity and quality in natural language generation
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Adaptive nearest neighbor machine translation
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Quality-aware decoding for neural machine translation
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Findings of the 2022 conference on machine translation (wmt22)
Tom Kocmi, Rachel Bawden, Ondřej Bojar, Anton Dvorkovich, Christian Federmann, Mark Fishel, Thamme Gowda, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Rebecca Knowles, Philipp Koehn, Christof Monz, Makoto Morishita, Masaaki Nagata, Toshiaki Nakazawa, Michal Novák, Martin Popel, Maja Popović, and Mariya Shmatova. 2022 · 2022
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Fast nearest neighbor machine translation
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JParaCrawl v3.0: A large-scale English-Japanese parallel corpus
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Efficient cluster-based k k -nearest-neighbor machine translation
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Nearest neighbor knowledge distillation for neural machine translation
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Subset retrieval nearest neighbor machine translation
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