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Revealing the robustness issues of natural language processing models and improving their robustness is important to their performance under difficult situations.
Paws: Paraphrase adversaries from word scrambling
Yuan Zhang, Jason Baldridge, and Luheng He. 2019b · 1904
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Is bert really robust? natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2019 · 1907
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Plagiarism in natural and programming languages: an overview of current tools and technologies
Paul Clough. 2000 · 2000
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Automatically constructing a corpus of sentential paraphrases
William B Dolan and Chris Brockett. 2005 · 2005
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Natural language processing with Python: analyzing text with the natural language toolkit
Steven Bird, Ewan Klein, and Edward Loper. 2009 · 2009
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Dynamic pooling and unfolding recursive autoencoders for paraphrase detection
Richard Socher, Eric H Huang, Jeffrey Pennin, Christopher D Manning, and Andrew Y Ng. 2011 · 2011
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Text matching as image recognition
Liang Pang, Yanyan Lan, Jiafeng Guo, Jun Xu, Shengxian Wan, and Xueqi Cheng. 2016 · 2016
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Supervised learning of universal sentence representations from natural language inference data
Alexis Conneau, Douwe Kiela, Holger Schwenk, Loïc Barrault, and Antoine Bordes. 2017 · 2017
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Natural language inference over interaction space
Yichen Gong, Heng Luo, and Jian Zhang. 2017 · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger. 2017 · 2017
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First quora dataset release: Question pairs
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Bilateral multi-perspective matching for natural language sentences
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Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang. 2018 · 2018
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Using adversarial examples in natural language processing
Petr Bělohlávek, Ondřej Plátek, Zdeněk Žabokrtskỳ, and Milan Straka. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
Adversarial examples for natural language classification problems
Volodymyr Kuleshov, Shantanu Thakoor, Tingfung Lau, and Stefano Ermon. 2018 · 2018
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Adversarially regularising neural nli models to integrate logical background knowledge
Pasquale Minervini and Sebastian Riedel. 2018 · 2018
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Semantically equivalent adversarial rules for debugging nlp models
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2018 · 2018
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Greedy attack and gumbel attack: Generating adversarial examples for discrete data
Puyudi Yang, Jianbo Chen, Cho-Jui Hsieh, Jane-Ling Wang, and Michael I Jordan. 2018 · 2018
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Wikiqa: A challenge dataset for open-domain question answering
Yi Yang, Wen-tau Yih, and Christopher Meek. 2015 · 2018
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Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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Attention-fused deep matching network for natural language inference
Chaoqun Duan, Lei Cui, Xinchi Chen, Furu Wei, Conghui Zhu, and Tiejun Zhao. 2018 · 2018
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Hotflip: White-box adversarial examples for text classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 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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Adversarial example generation with syntactically controlled paraphrase networks
Mohit Iyyer, John Wieting, Kevin Gimpel, and Luke Zettlemoyer. 2018 · 2018
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Semantic sentence matching with densely-connected recurrent and co-attentive information
Seonhoon Kim, Jin-Hyuk Hong, Inho Kang, and Nojun Kwak. 2018 · 2018
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Generating fluent adversarial examples for natural languages
Huangzhao Zhang, Hao Zhou, Ning Miao, and Lei Li. 2019a
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On the robustness of self-attentive models
Yu-Lun Hsieh, Minhao Cheng, Da-Cheng Juan, Wei Wei, Wen-Lian Hsu, and Cho-Jui Hsieh. 2019 · 2019
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Generating natural language adversarial examples through probability weighted word saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che. 2019 · 2019
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Paws-x: A cross-lingual adversarial dataset for paraphrase identification
Yinfei Yang, Yuan Zhang, Chris Tar, and Jason Baldridge. 2019 · 2019
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Adversarial examples for evaluating reading comprehension systems
Robin Jia and Percy Liang. 2017 · 2031
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Convolutional neural network architectures for matching natural language sentences
Baotian Hu, Zhengdong Lu, Hang Li, and Qingcai Chen. 2014 · 2050
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