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Paraphrasing exemplifies the ability to abstract semantic content from surface forms.
Unified techniques for vector quantization and hidden markov modeling using semi-continuous models
J. B. Macqueen. 1967 · 1967
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Paraphrasing using given and new information in a question-answer system
Kathleen R McKeown. 1980 · 1980
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Strategies for effective paraphrasing
Marie Meteer and Varda Shaked. 1988 · 1988
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Building a question answering test collection
Ellen M Voorhees and Dawn M Tice. 2000 · 2000
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Extracting paraphrases from a parallel corpus
Regina Barzilay and Kathleen R McKeown. 2001 · 2001
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Multiple-translation Chinese corpus
Shudong Huang, David Graff, and George Doddington. 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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Learning to paraphrase: an unsupervised approach using multiple-sequence alignment
Regina Barzilay and Lillian Lee. 2003 · 2003
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Syntax-based alignment of multiple translations: Extracting paraphrases and generating new sentences
Bo Pang, Kevin Knight, and Daniel Marcu. 2003 · 2003
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Unsupervised construction of large paraphrase corpora: Exploiting massively parallel news sources
Bill Dolan, Chris Quirk, and Chris Brockett. 2004 · 2004
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Paraphrasing with bilingual parallel corpora
Colin Bannard and Chris Callison-Burch. 2005 · 2005
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Automatically constructing a corpus of sentential paraphrases
William B Dolan and Chris Brockett. 2005 · 2005
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Paraphrasing and translation
Christopher Callison-Burch. 2007 · 2007
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Improved statistical machine translation using monolingually-derived paraphrases
Yuval Marton, Chris Callison-Burch, and Philip Resnik. 2009 · 2009
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Hitting the right paraphrases in good time
Stanley Kok and Chris Brockett. 2010 · 2010
Cited alongside, same era.
Generating phrasal and sentential paraphrases: A survey of data-driven methods
Nitin Madnani and Bonnie J. Dorr. 2010 · 2010
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
Pascal Vincent, Hugo Larochelle, Isabelle Lajoie, Yoshua Bengio, and Pierre-Antoine Manzagol. 2010 · 2010
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Joint learning of a dual smt system for paraphrase generation
Hong Sun and Ming Zhou. 2012 · 2012
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Baselines and bigrams: Simple, good sentiment and topic classification
Sida Wang and Christopher D Manning. 2012 · 2012
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One billion word benchmark for measuring progress in statistical language modeling
Semeval-2017 task 1: Semantic textual similarity-multilingual and cross-lingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Inigo Lopez-Gazpio, and Lucia Specia. 2017 · 2017
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Paraphrase generation with deep reinforcement learning
Zichao Li, Xin Jiang, Lifeng Shang, and Hang Li. 2017 · 2017
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Paraphrasing revisited with neural machine translation
Jonathan Mallinson, Rico Sennrich, and Mirella Lapata. 2017 · 2017
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Neural discrete representation learning
Aäron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu. 2017 · 2017
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Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson. 2013 · 2013
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Ng, and Christopher Potts. 2013 · 2013
Cited alongside, same era.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
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On the properties of neural machine translation: Encoder-decoder approaches
Kyunghyun Cho, Bart Van Merriënboer, Dzmitry Bahdanau, and Yoshua Bengio. 2014 · 2014
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deltableu: A discriminative metric for generation tasks with intrinsically diverse targets
Michel Galley, Chris Brockett, Alessandro Sordoni, Yangfeng Ji, Michael Auli, Chris Quirk, Margaret Mitchell, Jianfeng Gao, and Bill Dolan. 2015 · 2015
Cited alongside, same era.
Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Generating sentences from a continuous space
Samuel R. Bowman, Luke Vilnis, Oriol Vinyals, Andrew M. Dai, Rafal Józefowicz, and Samy Bengio. 2016 · 2016
Cited alongside, same era.
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Unsupervised neural machine translation
Mikel Artetxe, Gorka Labaka, Eneko Agirre, and Kyunghyun Cho. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Quickedit: Editing text & translations by crossing words out
David Grangier and Michael Auli. 2018 · 2018
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A deep generative framework for paraphrase generation
Ankush Gupta, Arvind Agarwal, Prawaan Singh, and Piyush Rai. 2018 · 2018
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Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
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Fast decoding in sequence models using discrete latent variables
Łukasz Kaiser, Aurko Roy, Ashish Vaswani, Niki Pamar, Samy Bengio, Jakob Uszkoreit, and Noam Shazeer. 2018 · 2018
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Theory and experiments on vector quantized autoencoders
Aurko Roy, Ashish Vaswani, Arvind Neelakantan, and Niki Parmar. 2018 · 2018
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Tensor2tensor for neural machine translation
Ashish Vaswani, Samy Bengio, Eugene Brevdo, Francois Chollet, Aidan N Gomez, Stephan Gouws, Llion Jones, Łukasz Kaiser, Nal Kalchbrenner, Niki Parmar, et al. 2018 · 2018
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Paranmt-50m: Pushing the limits of paraphrastic sentence embeddings with millions of machine translations
John Wieting and Kevin Gimpel. 2018 · 2018
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Qanet: Combining local convolution with global self-attention for reading comprehension
Adams Wei Yu, David Dohan, Minh-Thang Luong, Rui Zhao, Kai Chen, Mohammad Norouzi, and Quoc V Le. 2018 · 2018
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