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Deep neural networks (DNNs) are vulnerable to adversarial examples, perturbations to correctly classified examples which can cause the model to misclassify.
Parallel genetic algorithms, population genetics and combinatorial optimization
Heinz Mühlenbein. 1989 · 1989
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Genetic algorithms for combinatorial optimization: the assemble line balancing problem
Edward J Anderson and Michael C Ferris. 1994 · 1994
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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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One billion word benchmark for measuring progress in statistical language modeling
Ciprian Chelba, Tomas Mikolov, Mike Schuster, Qi Ge, Thorsten Brants, Phillipp Koehn, and Tony Robinson. 2013 · 2013
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Intriguing properties of neural networks
Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, and Rob Fergus. 2013 · 2013
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014 · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Christopher Manning. 2014 · 2014
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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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Adversarial machine learning at scale
A. Kurakin, I. Goodfellow, and S. Bengio. 2016 · 2016
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Counter-fitting word vectors to linguistic constraints
Nikola Mrkšić, Diarmuid O Séaghdha, Blaise Thomson, Milica Gašić, Lina Rojas-Barahona, Pei-Hao Su, David Vandyke, Tsung-Hsien Wen, and Steve Young. 2016 · 2016
Cited alongside, same era.
Towards evaluating the robustness of neural networks
N. Carlini and D. Wagner. 2017 · 2017
Cited alongside, same era.
Adversarial examples for evaluating reading comprehension systems
Genattack: Practical black-box attacks with gradient-free optimization
M. Alzantot, Y. Sharma, S. Chakraborty, and M. Srivastava. 2018 · 2018
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Audio adversarial examples: Targeted attacks on speech-to-text
Nicholas Carlini and David Wagner. 2018 · 2018
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Hotflip: White-box adversarial examples for text classification
J. Ebrahimi, A. Rao, D. Lowd, and D. Dou. 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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Adversarial examples for natural language classification problems
V. Kuleshov, S. Thakoor, T. Lau, and S. Ermon. 2018 · 2018
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Robin Jia and Percy Liang. 2017 · 2017
Cited alongside, same era.
Towards deep learning models resistant to adversarial attacks
A. Madry, A. Makelov, L. Schmidt, D. Tsipras, and A. Vladu. 2017 · 2017
Cited alongside, same era.
Attacking the madry defense model with l1-based adversarial examples
Y. Sharma and P. Y. Chen. 2017 · 2017
Cited alongside, same era.
P. Chen, H Zhang, Y. Sharma, J. Yi, and C. Hseih. 2017a
Cited in the paper.
Ead: Elastic-net attacks to deep neural networks via adversarial examples
P. Y. Chen, Y. Sharma, H. Zhang, J. Yi, and C. Hsieh. 2017b
Cited in the paper.
Enhanced lstm for natural language inference
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Si Wei, Hui Jiang, and Diana Inkpen. 2017c
Cited in the paper.
Practical black-box attacks against machine learning
N. Papernot, P. McDaniel, I. Goodfellow, S. Jha, Z. Celik, and A. Swami. 2016a
Cited in the paper.
Crafting adversarial input sequences for recurrent neural networks
N. Papernot, P. McDaniel, A. Swami, and R. Harang. 2016b
Cited in the paper.
Semantically equivalent adversarial rules for debugging nlp models
Marco Tulio Ribeiro, Sameer Singh, and Carlos Guestrin. 2018 · 2018
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Generating natural adversarial examples
Zhengli Zhao, Dheeru Dua, and Sameer Singh. 2018 · 2018
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