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We propose a novel data augmentation method for labeled sentences called conditional BERT contextual augmentation.
“cloze procedure”: A new tool for measuring readability
Wilson L Taylor. 1953 · 1953
Earlier work this paper cites.
Dropout: a simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov. 2014 · 1958
Earlier work this paper cites.
Wordnet: a lexical database for english
George A Miller. 1995 · 1995
Earlier work this paper cites.
Transformation invariance in pattern recognition—tangent distance and tangent propagation
Patrice Y Simard, Yann A LeCun, John S Denker, and Bernard Victorri. 1998 · 1998
Earlier work this paper cites.
Learning question classifiers
Xin Li and Dan Roth. 2002 · 2002
Earlier work this paper cites.
A sentimental education: Sentiment analysis using subjectivity summarization based on minimum cuts
Bo Pang and Lillian Lee. 2004 · 2004
Earlier work this paper cites.
Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales
Bo Pang and Lillian Lee. 2005 · 2005
Earlier work this paper cites.
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Janyce Wiebe, Theresa Wilson, and Claire Cardie. 2005 · 2005
Earlier work this paper cites.
Semi-supervised semantic role labeling using the latent words language model
Koen Deschacht and Marie-Francine Moens. 2009 · 2009
Earlier work this paper cites.
Model-portability experiments for textual temporal analysis
Oleksandr Kolomiyets, Steven Bethard, and Marie-Francine Moens. 2011 · 2011
Earlier work this paper cites.
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Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton. 2012 · 2012
Earlier work this paper cites.
Vocal tract length perturbation (vtlp) improves speech recognition
Navdeep Jaitly and Geoffrey E Hinton. 2013 · 2013
Earlier work this paper cites.
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Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Ng, and Christopher Potts. 2013 · 2013
Cited alongside, same era.
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Ian Goodfellow, Jean Pouget-Abadie, Mehdi Mirza, Bing Xu, David Warde-Farley, Sherjil Ozair, Aaron Courville, and Yoshua Bengio. 2014 · 2014
Cited alongside, same era.
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Cited alongside, same era.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Cited alongside, same era.
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Samuel R Bowman, Luke Vilnis, Oriol Vinyals, Andrew M Dai, Rafal Jozefowicz, and Samy Bengio. 2015 · 2015
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Marzieh Fadaee, Arianna Bisazza, and Christof Monz. 2017 · 2017
Later among the works it cites.
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Zhiting Hu, Zichao Yang, Xiaodan Liang, Ruslan Salakhutdinov, and Eric P Xing. 2017 · 2017
Later among the works it cites.
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Robin Jia and Percy Liang. 2017 · 2017
Later among the works it cites.
Data noising as smoothing in neural network language models
Ziang Xie, Sida I Wang, Jiwei Li, Daniel Lévy, Aiming Nie, Dan Jurafsky, and Andrew Y Ng. 2017 · 2017
Later among the works it cites.
Bert: Pre-training of deep bidirectional transformers for language understanding
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Cited alongside, same era.
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