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We study an important and challenging task of attacking natural language processing models in a hard label black box setting.
Is bert really robust? natural language attack on text classification and entailment
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A Context Aware Approach for Generating Natural Language Attacks
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Intriguing properties of neural networks
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Convolutional neural networks for speech recognition
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A large annotated corpus for learning natural language inference
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Character-level convolutional networks for text classification
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Enhanced lstm for natural language inference
Chen, Q.; Zhu, X.; Ling, Z.; Wei, S.; Jiang, H.; and Inkpen, D. 2016 · 2016
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Mining keystroke timing pattern for user authentication
Maheshwary, S.; and Pudi, V. 2016 · 2016
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Counter-fitting word vectors to linguistic constraints
Mrkšić, N.; Séaghdha, D. O.; Thomson, B.; Gašić, M.; Rojas-Barahona, L.; Su, P.-H.; Vandyke, D.; Wen, T.-H.; and Young, S. 2016 · 2016
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Generating natural language adversarial examples
Alzantot, M.; Sharma, Y.; Elgohary, A.; Ho, B.-J.; Srivastava, M.; and Chang, K.-W. 2018 · 2018
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Decision-Based Adversarial Attacks: Reliable Attacks Against Black-Box Machine Learning Models
Brendel, W.; Rauber, J.; and Bethge, M. 2018 · 2018
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Query-efficient hard-label black-box attack: An optimization-based approach
Cheng, M.; Le, T.; Chen, P.-Y.; Yi, J.; Zhang, H.; and Hsieh, C.-J. 2018 · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding
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Supervised learning of universal sentence representations from natural language inference data
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Hotflip: White-box adversarial examples for text classification
Ebrahimi, J.; Rao, A.; Lowd, D.; and Dou, D. 2017 · 2017
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Deep text classification can be fooled
Liang, B.; Li, H.; Su, M.; Bian, P.; Li, X.; and Shi, W. 2017 · 2017
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Deep secure: A fast and simple neural network based approach for user authentication and identification via keystroke dynamics
Maheshwary, S.; Ganguly, S.; and Pudi, V. 2017 · 2017
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Practical black-box attacks against machine learning
Papernot, N.; McDaniel, P.; Goodfellow, I.; Jha, S.; Celik, Z. B.; and Swami, A. 2017 · 2017
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A broad-coverage challenge corpus for sentence understanding through inference
Williams, A.; Nangia, N.; and Bowman, S. R. 2017 · 2017
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Generating natural adversarial examples
Zhao, Z.; Dua, D.; and Singh, S. 2017 · 2017
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Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
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Black-box generation of adversarial text sequences to evade deep learning classifiers
Gao, J.; Lanchantin, J.; Soffa, M. L.; and Qi, Y. 2018 · 2018
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Textbugger: Generating adversarial text against real-world applications
Li, J.; Ji, S.; Du, T.; Li, B.; and Wang, T. 2018 · 2018
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Matching resumes to jobs via deep siamese network
Maheshwary, S.; and Misra, H. 2018 · 2018
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Recent trends in deep learning based natural language processing
Young, T.; Hazarika, D.; Poria, S.; and Cambria, E. 2018 · 2018
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Generating natural language adversarial examples through probability weighted word saliency
Ren, S.; Deng, Y.; He, K.; and Che, W. 2019 · 2019
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Generating Fluent Adversarial Examples for Natural Languages
Zhang, H.; Zhou, H.; Miao, N.; and Li, L. 2019 · 2019
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Word-level Textual Adversarial Attacking as Combinatorial Optimization
Zang, Y.; Qi, F.; Yang, C.; Liu, Z.; Zhang, M.; Liu, Q.; and Sun, M. 2020 · 2020
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