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Word-level adversarial attacks have shown success in NLP models, drastically decreasing the performance of transformer-based models in recent years.
Roberta: A robustly optimized bert pretraining approach
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Convolutional neural networks for sentence classification
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Character-level convolutional networks for text classification
Xiang Zhang, Junbo Zhao, and Yann LeCun. 2015 · 2015
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Counter-fitting word vectors to linguistic constraints
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Adversarial examples are not easily detected: Bypassing ten detection methods
Nicholas Carlini and David Wagner. 2017 · 2017
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On the (statistical) detection of adversarial examples
Kathrin Grosse, Praveen Manoharan, Nicolas Papernot, Michael Backes, and Patrick McDaniel. 2017 · 2017
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On detecting adversarial perturbations
Jan Hendrik Metzen, Tim Genewein, Volker Fischer, and Bastian Bischoff. 2017 · 2017
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Learning to discriminate perturbations for blocking adversarial attacks in text classification
Yichao Zhou, Jyun-Yu Jiang, Kai-Wei Chang, and Wei Wang. 2019 · 2019
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Bae: Bert-based adversarial examples for text classification
Siddhant Garg and Goutham Ramakrishnan. 2020 · 2020
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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
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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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Bert-attack: Adversarial attack against bert using bert
Linyang Li, Ruotian Ma, Qipeng Guo, Xiangyang Xue, and Xipeng Qiu. 2020 · 2020
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Reevaluating adversarial examples in natural language
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Daniel Cer, Yinfei Yang, Sheng-yi Kong, Nan Hua, Nicole Limtiaco, Rhomni St John, Noah Constant, Mario Guajardo-Céspedes, Steve Yuan, Chris Tar, et al. 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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Minimum covariance determinant and extensions
Mia Hubert, Michiel Debruyne, and Peter J Rousseeuw. 2018 · 2018
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A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin. 2018 · 2018
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Feature squeezing: Detecting adversarial examples in deep neural networks
Weilin Xu, David Evans, and Yanjun Qi. 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, Ilya Sutskever, et al. 2019 · 2019
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John Morris, Eli Lifland, Jack Lanchantin, Yangfeng Ji, and Yanjun Qi. 2020a · 2020
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Textattack: A framework for adversarial attacks, data augmentation, and adversarial training in nlp
John Morris, Eli Lifland, Jin Yong Yoo, Jake Grigsby, Di Jin, and Yanjun Qi. 2020b · 2020
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Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander M. Rush. 2020 · 2020
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Adversarial attacks on deep-learning models in natural language processing: A survey
Wei Emma Zhang, Quan Z Sheng, Ahoud Alhazmi, and Chenliang Li. 2020 · 2020
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Rongzhou Bao, Jiayi Wang, and Hai Zhao. 2021 · 2021
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BERT-defense: A probabilistic model based on BERT to combat cognitively inspired orthographic adversarial attacks
Yannik Keller, Jan Mackensen, and Steffen Eger. 2021 · 2021
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A sweet rabbit hole by darcy: Using honeypots to detect universal trigger’s adversarial attacks
Thai Le, Noseong Park, and Dongwon Lee. 2021 · 2021
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Frequency-guided word substitutions for detecting textual adversarial examples
Maximilian Mozes, Pontus Stenetorp, Bennett Kleinberg, and Lewis Griffin. 2021 · 2021
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Defense against synonym substitution-based adversarial attacks via dirichlet neighborhood ensemble
Yi Zhou, Xiaoqing Zheng, Cho-Jui Hsieh, Kai-Wei Chang, and Xuan-Jing Huang. 2021 · 2021
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