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Training a model for grammatical error correction (GEC) requires a set of labeled ungrammatical / grammatical sentence pairs, but manually annotating such pairs can be expensive.
Scaling laws for neural language models
Jared Kaplan, Sam McCandlish, Tom Henighan, Tom B Brown, Benjamin Chess, Rewon Child, Scott Gray, Alec Radford, Jeffrey Wu, and Dario Amodei. 2020 · 2001
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The cambridge learner corpus: Error coding and analysis for lexicography and elt
Diane Nicholls. 2003 · 2003
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Searching for grammaticality: Propagating dependencies in the viterbi algorithm
Stephen Wan, Robert Dale, and Mark Dras. 2005 · 2005
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Domain adaptation for statistical classifiers
Hal Daume III and Daniel Marcu. 2006 · 2006
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Gleu: Automatic evaluation of sentence-level fluency
Andrew Mutton, Mark Dras, Stephen Wan, and Robert Dale. 2007 · 2007
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On automated evaluation of readability of summaries: Capturing grammaticality, focus, structure and coherence
Ravikiran Vadlapudi and Rahul Katragadda. 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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A new dataset and method for automatically grading esol texts
Helen Yannakoudakis, Ted Briscoe, and Ben Medlock. 2011 · 2011
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Better evaluation for grammatical error correction
Daniel Dahlmeier and Hwee Tou Ng. 2012 · 2012
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Tense and aspect error correction for esl learners using global context
Toshikazu Tajiri, Mamoru Komachi, and Yuji Matsumoto. 2012 · 2012
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One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson. 2013 · 2013
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Building a large annotated corpus of learner english: The nus corpus of learner english
Daniel Dahlmeier, Hwee Tou Ng, and Siew Mei Wu. 2013 · 2013
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On the difficulty of training recurrent neural networks
Razvan Pascanu, Tomas Mikolov, and Yoshua Bengio. 2013 · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2013 · 2013
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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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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
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Towards a standard evaluation method for grammatical error detection and correction
Mariano Felice and Ted Briscoe. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik Kingma and Jimmy Ba. 2015 · 2015
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Ground truth for grammatical error correction metrics
Courtney Napoles, Keisuke Sakaguchi, Matt Post, and Joel Tetreault. 2015 · 2015
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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There’s no comparison: Reference-less evaluation metrics in grammatical error correction
Courtney Napoles, Keisuke Sakaguchi, and Joel Tetreault. 2016 · 2016
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Improving neural machine translation models with monolingual data
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Neural language correction with character-based attention
Ziang Xie, Anand Avati, Naveen Arivazhagan, Dan Jurafsky, and Andrew Y Ng. 2016 · 2016
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Grammatical error correction using neural machine translation
Zheng Yuan and Ted Briscoe. 2016 · 2016
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Automatic annotation and evaluation of error types for grammatical error correction
Christopher Bryant, Mariano Felice, and Edward Briscoe. 2017 · 2017
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A nested attention neural hybrid model for grammatical error correction
Jianshu Ji, Qinlong Wang, Kristina Toutanova, Yongen Gong, Steven Truong, and Jianfeng Gao. 2017 · 2017
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An empirical study of incorporating pseudo data into grammatical error correction
Shun Kiyono, Jun Suzuki, Masato Mita, Tomoya Mizumoto, and Kentaro Inui. 2019 · 2019
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Corpora generation for grammatical error correction
Jared Lichtarge, Chris Alberti, Shankar Kumar, Noam Shazeer, Niki Parmar, and Simon Tong. 2019 · 2019
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Cross-corpora evaluation and analysis of grammatical error correction models—is single-corpus evaluation enough?
Masato Mita, Tomoya Mizumoto, Masahiro Kaneko, Ryo Nagata, and Kentaro Inui. 2019 · 2019
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Grammatical error correction in low-resource scenarios
Jakub Náplava and Milan Straka. 2019 · 2019
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Enabling robust grammatical error correction in new domains: Data sets, metrics, and analyses
Courtney Napoles, Maria Nădejde, and Joel Tetreault. 2019 · 2019
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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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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
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A multilayer convolutional encoder-decoder neural network for grammatical error correction
Shamil Chollampatt and Hwee Tou Ng. 2018 · 2018
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Fluency boost learning and inference for neural grammatical error correction
Tao Ge, Furu Wei, and Ming Zhou. 2018 · 2018
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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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Sentence-level fluency evaluation: References help, but can be spared!
Katharina Kann, Sascha Rothe, and Katja Filippova. 2018 · 2018
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Unsupervised machine translation using monolingual corpora only
Guillaume Lample, Alexis Conneau, Ludovic Denoyer, and Marc’Aurelio Ranzato. 2018 · 2018
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Combating adversarial misspellings with robust word recognition
Danish Pruthi, Bhuwan Dhingra, and Zachary C Lipton. 2019 · 2019
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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Neural grammatical error correction with finite state transducers
Felix Stahlberg, Christopher Bryant, and Bill Byrne. 2019 · 2019
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Bert rediscovers the classical nlp pipeline
Ian Tenney, Dipanjan Das, and Ellie Pavlick. 2019 · 2019
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Universal adversarial triggers for attacking and analyzing nlp
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh. 2019 · 2019
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Topiceq: A joint topic and mathematical equation model for scientific texts
Michihiro Yasunaga and John D Lafferty. 2019 · 2019
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Improving grammatical error correction via pre-training a copy-augmented architecture with unlabeled data
Wei Zhao, Liang Wang, Kewei Shen, Ruoyu Jia, and Jingming Liu. 2019 · 2019
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al. 2020 · 2020
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Unsupervised parsing via constituency tests
Steven Cao, Nikita Kitaev, and Dan Klein. 2020 · 2020
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Robust encodings: A framework for combating adversarial typos
Erik Jones, Robin Jia, Aditi Raghunathan, and Percy Liang. 2020 · 2020
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension
Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2020 · 2020
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Grammaticality and language modelling
Jingcheng Niu and Gerald Penn. 2020 · 2020
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Gector–grammatical error correction: Tag, not rewrite
Kostiantyn Omelianchuk, Vitaliy Atrasevych, Artem Chernodub, and Oleksandr Skurzhanskyi. 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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Break-It-Fix-It: Unsupervised Learning for Program Repair
Michihiro Yasunaga and Percy Liang. 2021 · 2021
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