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To combat adversarial spelling mistakes, we propose placing a word recognition model in front of the downstream classifier.
Generating natural adversarial examples
Zhengli Zhao, Dheeru Dua, and Sameer Singh. 2018 · 1905
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The significance of letter position in word recognition
Graham Ernest Rawlinson. 1976 · 1976
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Context based spelling correction
Eric Mays, Fred J. Damerau, and Robert L. Mercer. 1991 · 1991
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Techniques for automatically correcting words in text
Karen Kukich. 1992 · 1992
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An improved error model for noisy channel spelling correction
Eric Brill and Robert C. Moore. 2000 · 2000
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Psycholinguistic evidence on scrambled letters in reading
Matt Davis. 2003 · 2003
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Automatically constructing a corpus of sentential paraphrases
William B Dolan and Chris Brockett. 2005 · 2005
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Spam deobfuscation using a hidden markov model
Honglak Lee and Andrew Y Ng. 2005 · 2005
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Spam filtering based on the analysis of text information embedded into images
Giorgio Fumera, Ignazio Pillai, and Fabio Roli. 2006 · 2006
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Learning word vectors for sentiment analysis
Andrew L. Maas, Raymond E. Daly, Peter T. Pham, Dan Huang, Andrew Y. Ng, and Christopher Potts. 2011 · 2011
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
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Trends in transition from classical censorship to internet censorship: selected country overviews
Constance Bitso, Ina Fourie, and Theo JD Bothma. 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.
Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2013 · 2013
Cited alongside, same era.
Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014 · 2014
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, et al. 2016 · 2016
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2017
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Robsut wrod reocginiton via semi-character recurrent neural network
Keisuke Sakaguchi, Kevin Duh, Matt Post, and Benjamin Van Durme. 2017 · 2017
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Feature squeezing: Detecting adversarial examples in deep neural networks
Weilin Xu, David Evans, and Yanjun Qi. 2017 · 2017
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Synthetic and natural noise both break neural machine translation
Yonatan Belinkov and Yonatan Bisk. 2018 · 2018
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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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Understanding neural networks through representation erasure
Jiwei Li, Will Monroe, and Dan Jurafsky. 2016 · 2016
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SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Sentence-level grammatical error identification as sequence-to-sequence correction
Allen Schmaltz, Yoon Kim, Alexander M. Rush, and Stuart Shieber. 2016 · 2016
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On adversarial examples for character-level neural machine translation
Javid Ebrahimi, Daniel Lowd, and Dejing Dou. 2018a
Cited in the paper.
Hotflip: White-box adversarial examples for nlp
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 2018b
Cited in the paper.
Thermometer encoding: One hot way to resist adversarial examples
Jacob Buckman, Aurko Roy, Colin Raffel, and Ian Goodfellow. 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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Breaking nli systems with sentences that require simple lexical inferences
Max Glockner, Vered Shwartz, and Yoav Goldberg. 2018 · 2018
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Spelling error correction using a nested rnn model and pseudo training data
Hao Li, Yang Wang, Xinyu Liu, Zhichao Sheng, and Si Wei. 2018 · 2018
Later among the works it cites.