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Pretrained language models (PLMs) perform poorly under adversarial attacks.
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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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
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Character-level Convolutional Networks for Text Classification
Xiang Zhang, Junbo Jake Zhao, and Yann LeCun. 2015 · 2015
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Adversarial Training Methods for Semi-Supervised Text Classification
Takeru Miyato, Andrew M. Dai, and Ian J. Goodfellow. 2017 · 2017
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Generating natural language adversarial examples
Moustafa Alzantot, Yash Sharma, Ahmed Elgohary, Bo-Jhang Ho, Mani Srivastava, and Kai-Wei Chang · 2018
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mixup: Beyond empirical risk minimization
Hongyi Zhang, Moustapha Cissé, Yann N. Dauphin, and David Lopez-Paz. 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. 2019 · 2019
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Augmenting Data with Mixup for Sentence Classification: An Empirical Study
Hongyu Guo, Yongyi Mao, and Richong Zhang. 2019 · 2019
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Achieving verified robustness to symbol substitutions via interval bound propagation
Po-Sen Huang, Robert Stanforth, Johannes Welbl, Chris Dyer, Dani Yogatama, Sven Gowal, Krishnamurthy Dvijotham, and Pushmeet Kohli. 2019 · 2019
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Certified Robustness to Adversarial Word Substitutions
Robin Jia, Aditi Raghunathan, Kerem Göksel, and Percy Liang. 2019 · 2019
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Alex Lamb, Vikas Verma, Juho Kannala, and Yoshua Bengio. 2019 · 2019
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RoBERTa: A Robustly Optimized BERT Pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 2019
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Combating Adversarial Misspellings with Robust Word Recognition
Danish Pruthi, Bhuwan Dhingra, and Zachary C. Lipton. 2019 · 2019
Cited alongside, same era.
Generating Natural Language Adversarial Examples through Probability Weighted Word Saliency
Shuhuai Ren, Yihe Deng, Kun He, and Wanxiang Che. 2019 · 2019
Cited alongside, same era.
Generating Fluent Adversarial Examples for Natural Languages
Huangzhao Zhang, Hao Zhou, Ning Miao, and Lei Li. 2020 · 2019
Cited alongside, same era.
MixText: Linguistically-informed interpolation of hidden space for semi-supervised text classification
Jiaao Chen, Zichao Yang, and Diyi Yang. 2020 · 2020
Cited alongside, same era.
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou · 2020
Cited alongside, same era.
It’s morphin’ time! Combating linguistic discrimination with inflectional perturbations
Samson Tan, Shafiq Joty, Min-Yen Kan, and Richard Socher. 2020 · 2020
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T3: Tree-autoencoder constrained adversarial text generation for targeted attack
Boxin Wang, Hengzhi Pei, Boyuan Pan, Qian Chen, Shuohang Wang, and Bo Li. 2020a · 2020
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CAT-gen: Improving robustness in NLP models via controlled adversarial text generation
Tianlu Wang, Xuezhi Wang, Yao Qin, Ben Packer, Kang Li, Jilin Chen, Alex Beutel, and Ed Chi. 2020b · 2020
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On the Robustness of Language Encoders against Grammatical Errors
Fan Yin, Quanyu Long, Tao Meng, and Kai-Wei Chang. 2020 · 2020
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Word-level Textual Adversarial Attacking as Combinatorial Optimization
Yuan Zang, Fanchao Qi, Chenghao Yang, Zhiyuan Liu, Meng Zhang, Qun Liu, and Maosong Sun. 2020 · 2020
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BAE: BERT-based adversarial examples for text classification
Siddhant Garg and Goutham Ramakrishnan. 2020 · 2020
Cited alongside, same era.
Is BERT really robust? A strong baseline for natural language attack on text classification and entailment
Di Jin, Zhijing Jin, Joey Tianyi Zhou, and Peter Szolovits. 2020 · 2020
Cited alongside, same era.
Robust Encodings: A Framework for Combating Adversarial Typos
Erik Jones, Robin Jia, Aditi Raghunathan, and Percy Liang. 2020 · 2020
Cited alongside, same era.
ALBERT: A lite BERT for self-supervised learning of language representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Cited alongside, same era.
BERT-ATTACK: Adversarial attack against BERT using BERT
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu. 2020 · 2020
Cited alongside, same era.
CharBERT: Character-aware pre-trained language model
Wentao Ma, Yiming Cui, Chenglei Si, Ting Liu, Shijin Wang, and Guoping Hu. 2020 · 2020
Cited alongside, same era.
Mixup inference: Better exploiting mixup to defend adversarial attacks
Tianyu Pang, Kun Xu, and Jun Zhu. 2020 · 2020
Cited alongside, same era.
Evaluating and enhancing the robustness of neural network-based dependency parsing models with adversarial examples
Xiaoqing Zheng, Jiehang Zeng, Yi Zhou, Cho-Jui Hsieh, Minhao Cheng, and Xuanjing Huang. 2020 · 2020
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A Reinforced Generation of Adversarial Samples for Neural Machine Translation
Wei Zou, Shujian Huang, John Xie, Xin-Yu Dai, and Jiajun Chen. 2020 · 2020
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TAVAT: Token-Aware Virtual Adversarial Training for Language Understanding
Linyang Li and Xipeng Qiu. 2021 · 2021
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Benchmarking Robustness of Machine Reading Comprehension Models
Chenglei Si, Ziqing Yang, Yiming Cui, Wentao Ma, Ting Liu, and Shijin Wang. 2021 · 2021
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InfoBERT: Improving Robustness of Language Models from An Information Theoretic Perspective
Boxin Wang, Shuohang Wang, Y. Cheng, Zhe Gan, Ruoxi Jia, Bo Li, and Jingjing Liu. 2021 · 2021
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How Does Mixup Help With Robustness and Generalization?
Linjun Zhang, Zhun Deng, Kenji Kawaguchi, Amirata Ghorbani, and James Zou. 2021 · 2021
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