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Grammatical Error Correction (GEC) has been recently modeled using the sequence-to-sequence framework.
Correcting ESL errors using phrasal SMT techniques
Chris Brockett, William B Dolan, and Michael Gamon. 2006 · 2006
Earlier work this paper cites.
Using automatic roundtrip translation to repair general errors in second language writing
A. Désilets and Hermet M. 2009 · 2009
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Generrate: Generating errors for use in grammatical error detection
Jennifer Foster and Øistein E. Andersen. 2009 · 2009
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Generating confusion sets for context-sensitive error correction
Alla Rozovskaya and Dan Roth. 2010 · 2010
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Mining revision log of language learning SNS for automated japanese error correction of second language learners
Tomoya Mizumoto, Mamoru Komachi, Masaaki Nagata, and Yuji Matsumoto. 2011 · 2011
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Exploring grammatical error correction with not-so-crummy machine translation
Nitin Madnani, Joel Tetreault, and Martin Chodorow. 2012 · 2012
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Japanese and korean voice search
Michael Schuster and Kaisuke Nakajima. 2012 · 2012
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Robust systems for preposition error correction using wikipedia revisions
Aoife Cahill, Nitin Madnani, Joel Tetreault, and Diane Napolitano. 2013 · 2013
Earlier work this paper cites.
Grammatical error correction using hybrid systems and type filtering
Mariano Felice, Zheng Yuan, Øistein E. Andersen, Helen Yannakoudakis, and Ekaterina Kochmar. 2014 · 2014
Earlier work this paper cites.
The wiked error corpus: A corpus of corrective wikipedia edits and its application to grammatical error correction
Roman Grundkiewicz and Marcin Junczys-Dowmunt. 2014 · 2014
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Predicting grammaticality on an ordinal scale
Michael Heilman, Aoife Cahill, Nitin Madnani, Melissa Lopez, Matthew Mulholland, and Joel Tetreault. 2014 · 2014
Earlier work this paper cites.
The CoNLL-2014 shared task on grammatical error correction
Hwee Tou Ng, Siew Mei Wu, Ted Briscoe, Christian Hadiwinoto, Raymond Hendy Susanto, and Christopher Bryant. 2014 · 2014
Earlier work this paper cites.
Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
Cited alongside, same era.
Stanford neural machine translation systems for spoken language domain
Minh-Thang Luong and Christopher D. Manning. 2015 · 2015
Cited alongside, same era.
Kyoto university participation to wat 2016
Fabian Cromieres, Chenhui Chu, Toshiaki Nakazawa, and Sadao Kurohashi. 2016 · 2016
Cited alongside, same era.
Phrase-based machine translation is state-of-the-art for automatic grammatical error correction
Marcin Junczys-Dowmunt and Roman Grundkiewicz. 2016 · 2016
Cited alongside, same era.
Courtney Napoles, Keisuke Sakaguchi, Matt Post, and Joel Tetreault. 2016 · 2016
Cited alongside, same era.
Grammatical error correction: Machine translation and classifiers
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
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Six challenges for neural machine translation
Philipp Koehn and Rebecca Knowles. 2017 · 2017
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JFLEG: A fluency corpus and benchmark for grammatical error correction
Courtney Napoles, Keisuke Sakaguchi, and Joel Tetreault. 2017 · 2017
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Artificial error generation with machine translation and syntactic patterns
Marek Rei, Mariano Felice, Zheng Yuan, and Ted Briscoe. 2017 · 2017
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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Alla Rozovskaya and Dan Roth. 2016 · 2016
Cited alongside, same era.
Simpitiki: a simplification corpus for italian
Sara Tonelli, Alessio Palmero Aprosio, and Francesca Saltori. 2016 · 2016
Cited alongside, same era.
Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V. Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, Jeff Klingner, Apurva Shah, Melvin Johnson, Xiaobing Liu, Łukasz Kaiser, Stephan Gouws, Yoshikiyo Kato, Taku Kudo, Hideto Kazawa, Keith Stevens, George Kurian, Nishant Patil, Wei Wang, Cliff Young, Jason Smith, Jason Riesa, Alex Rudnick, Oriol Vinyals, Greg Corrado, Macduff Hughes, and Jeffrey Dean. 2016 · 2016
Cited alongside, same era.
Neural language correction with character-based attention
Ziang Xie, Anand Avati, Naveen Arivazhagan, Dan Jurafsky, and Andrew Y Ng. 2016 · 2016
Cited alongside, same era.
Automatic annotation and evaluation of error types for grammatical error correction
Christopher Bryant, Mariano Felice, and Ted Briscoe. 2017 · 2017
Cited alongside, same era.
Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine. 2017 · 2017
Cited alongside, same era.
A beamsearch decoder for grammatical error correction
Daniel Dahlmeier and Hwee Tou Ng. 2012a
Cited in the paper.
Learning to split and rephrase from wikipedia edit history
Jan Botha, Manaal Faruqui, John Alex, Jason Baldridge, and Dipanjan Das. 2018 · 2018
Later among the works it cites.
A multilayer convolutional encoder-decoder neural network for grammatical error correction
Shamil Chollampatt and Hwee Tou Ng. 2018 · 2018
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Near human-level performance in grammatical error correction with hybrid machine translation
Roman Grundkiewicz and Marcin Junczys-Dowmunt. 2018 · 2018
Later among the works it cites.
Approaching neural grammatical error correction as a low-resource machine translation task
Marcin Junczys-Dowmunt, Roman Grundkiewicz, Shubha Guha, and Kenneth Heafield. 2018 · 2018
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Adafactor: Adaptive learning rates with sublinear memory cost
Noam Shazeer and Mitchell Stern. 2018 · 2018
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Noising and denoising natural language: Diverse backtranslation for grammar correction
Ziang Xie Xie, Guillaume Genthial, Stanley Xie, Andrew Ng, and Dan Jurafsky. 2018 · 2018
Later among the works it cites.