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Recent work has shown that a multilingual neural machine translation (NMT) model can be used to judge how well a sentence paraphrases another sentence in the same language (Thompson and Post, 2020); however, attempting to generate paraphrases from such a model using standard beam search produces trivial copies or near copies.
Wikimatrix: Mining 135m parallel sentences in 1620 language pairs from wikipedia
Holger Schwenk, Vishrav Chaudhary, Shuo Sun, Hongyu Gong, and Francisco Guzmán. 2019 · 1907
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Paraphrasing questions using given and new information
Kathleen R. McKeown. 1983 · 1983
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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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Monolingual machine translation for paraphrase generation
Chris Quirk, Chris Brockett, and William Dolan. 2004 · 2004
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METEOR: An automatic metric for MT evaluation with improved correlation with human judgments
Satanjeev Banerjee and Alon Lavie. 2005 · 2005
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Europarl: A parallel corpus for statistical machine translation
Philipp Koehn. 2005 · 2005
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ParaEval: Using paraphrases to evaluate summaries automatically
Liang Zhou, Chin-Yew Lin, Dragos Stefan Munteanu, and Eduard Hovy. 2006 · 2006
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Extending the METEOR machine translation evaluation metric to the phrase level
Michael Denkowski and Alon Lavie. 2010 · 2010
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Multilingual WSD-like constraints for paraphrase extraction
Wilker Aziz and Lucia Specia. 2013 · 2013
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Squibs: What is a paraphrase?
Rahul Bhagat and Eduard Hovy. 2013 · 2013
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Findings of the 2013 Workshop on Statistical Machine Translation
Ondřej Bojar, Christian Buck, Chris Callison-Burch, Christian Federmann, Barry Haddow, Philipp Koehn, Christof Monz, Matt Post, Radu Soricut, and Lucia Specia. 2013 · 2013
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Multi-task learning for multiple language translation
Daxiang Dong, Hua Wu, Wei He, Dianhai Yu, and Haifeng Wang. 2015 · 2015
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Results of the WMT16 metrics shared task
Ondřej Bojar, Yvette Graham, Amir Kamran, and Miloš Stanojević. 2016 · 2016
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Learning to paraphrase for question answering
Li Dong, Jonathan Mallinson, Siva Reddy, and Mirella Lapata. 2017 · 2017
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Lexically constrained decoding for sequence generation using grid beam search
Chris Hokamp and Qun Liu. 2017 · 2017
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Google’s multilingual neural machine translation system: Enabling zero-shot translation
Melvin Johnson, Mike Schuster, Quoc V. Le, Maxim Krikun, Yonghui Wu, Zhifeng Chen, Nikhil Thorat, Fernanda Viégas, Martin Wattenberg, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2017 · 2017
Cited alongside, same era.
Paraphrasing revisited with neural machine translation
Jonathan Mallinson, Rico Sennrich, and Mirella Lapata. 2017 · 2017
Cited alongside, same era.
Learning joint multilingual sentence representations with neural machine translation
Holger Schwenk and Matthijs Douze. 2017 · 2017
Cited alongside, same era.
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
Cited alongside, same era.
Learning paraphrastic sentence embeddings from back-translated bitext
John Wieting, Jonathan Mallinson, and Kevin Gimpel. 2017 · 2017
Cited alongside, same era.
A multi-task approach for disentangling syntax and semantics in sentence representations
Mingda Chen, Qingming Tang, Sam Wiseman, and Kevin Gimpel. 2019b · 2019
Later among the works it cites.
Improving the robustness of question answering systems to question paraphrasing
Wee Chung Gan and Hwee Tou Ng. 2019 · 2019
Later among the works it cites.
Improved lexically constrained decoding for translation and monolingual rewriting
J. Edward Hu, Huda Khayrallah, Ryan Culkin, Patrick Xia, Tongfei Chen, Matt Post, and Benjamin Van Durme. 2019a · 2019
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Negative lexically constrained decoding for paraphrase generation
Tomoyuki Kajiwara. 2019 · 2019
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Automatically learning data augmentation policies for dialogue tasks
Tong Niu and Mohit Bansal. 2019 · 2019
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fairseq: A fast, extensible toolkit for sequence modeling
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Jiatao Gu, Hany Hassan, Jacob Devlin, and Victor O.K. Li. 2018 · 2018
Cited alongside, same era.
A deep generative framework for paraphrase generation
Ankush Gupta, Arvind Agarwal, Prawaan Singh, and Piyush Rai. 2018 · 2018
Cited alongside, same era.
Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
Cited alongside, same era.
SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
Cited alongside, same era.
Paraphrase generation with deep reinforcement learning
Zichao Li, Xin Jiang, Lifeng Shang, and Hang Li. 2018 · 2018
Cited alongside, same era.
Adversarial over-sensitivity and over-stability strategies for dialogue models
Tong Niu and Mohit Bansal. 2018 · 2018
Cited alongside, same era.
Fast lexically constrained decoding with dynamic beam allocation for neural machine translation
Matt Post and David Vilar. 2018 · 2018
Cited alongside, same era.
Myle Ott, Sergey Edunov, Alexei Baevski, Angela Fan, Sam Gross, Nathan Ng, David Grangier, and Michael Auli. 2019 · 2019
Later among the works it cites.
Improving zero-shot translation with language-independent constraints
Ngoc-Quan Pham, Jan Niehues, Thanh-Le Ha, and Alexander Waibel. 2019 · 2019
Later among the works it cites.
An evaluation of language-agnostic inner-attention-based representations in machine translation
Alessandro Raganato, Raúl Vázquez, Mathias Creutz, and Jörg Tiedemann. 2019 · 2019
Later among the works it cites.
Generating diverse translations with sentence codes
Raphael Shu, Hideki Nakayama, and Kyunghyun Cho. 2019 · 2019
Later among the works it cites.
Measuring semantic abstraction of multilingual NMT with paraphrase recognition and generation tasks
Jörg Tiedemann and Yves Scherrer. 2019 · 2019
Later among the works it cites.
Simple and effective paraphrastic similarity from parallel translations
John Wieting, Kevin Gimpel, Graham Neubig, and Taylor Berg-Kirkpatrick. 2019 · 2019
Later among the works it cites.
Paraphrases as foreign languages in multilingual neural machine translation
Zhong Zhou, Matthias Sperber, and Alexander Waibel. 2019 · 2019
Later among the works it cites.
Simulated multiple reference training improves low-resource machine translation
Huda Khayrallah, Brian Thompson, Matt Post, and Philipp Koehn. 2020 · 2020
Closest in time.
Automatic machine translation evaluation in many languages via zero-shot paraphrasing
Brian Thompson and Matt Post. 2020 · 2020
Closest in time.