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Deep learning models have been used widely for various purposes in recent years in object recognition, self-driving cars, face recognition, speech recognition, sentiment analysis, and many others.
A survey on adversarial attacks and defenses in text
Wenqi Wang, Benxiao Tang, Run Wang, Lina Wang, and Aoshuang Ye. 2019a · 1902
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On evaluation of adversarial perturbations for sequence-to-sequence models
Paul Michel, Xian Li, Graham Neubig, and Juan Miguel Pino. 2019 · 1903
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White-to-black: Efficient distillation of black-box adversarial attacks
Yotam Gil, Yoav Chai, Or Gorodissky, and Jonathan Berant. 2019 · 1904
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Combating adversarial misspellings with robust word recognition
Danish Pruthi, Bhuwan Dhingra, and Zachary C Lipton. 2019 · 1905
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Robust neural machine translation with doubly adversarial inputs
Yong Cheng, Lu Jiang, and Wolfgang Macherey. 2019 · 1906
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Universal adversarial triggers for nlp
Eric Wallace, Shi Feng, Nikhil Kandpal, Matt Gardner, and Sameer Singh. 2019 · 1908
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Natural language adversarial attacks and defenses in word level
Xiaosen Wang, Hao Jin, and Kun He. 2019b · 1909
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Adversarial attacks and defenses in images, graphs and text: A review
Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, and Anil Jain. 2019 · 1909
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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 · 1909
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Textual adversarial attack as combinatorial optimization
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Natural language watermarking: Design, analysis, and a proof-of-concept implementation
Mikhail J Atallah, Victor Raskin, Michael Crogan, Christian Hempelmann, Florian Kerschbaum, Dina Mohamed, and Sanket Naik. 2001 · 2001
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A neural probabilistic language model
Yoshua Bengio, Réjean Ducharme, Pascal Vincent, and Christian Jauvin. 2003 · 2003
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Fuzzing: brute force vulnerability discovery
Michael Sutton, Adam Greene, and Pedram Amini. 2007 · 2007
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Adversarial examples for natural language classification problems
V Kuleshov, S Thakoor, T Lau, and S Ermon. 2008 · 2008
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Opinion mining and sentiment analysis
Bo Pang and Lillian Lee. 2008 · 2008
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A review of computer vision techniques for the analysis of urban traffic
Norbert Buch, Sergio A Velastin, and James Orwell. 2011 · 2011
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A survey of text question answering techniques
Poonam Gupta and Vishal Gupta. 2012 · 2012
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Recent advances in deep learning for speech research at microsoft
Li Deng, Jinyu Li, Jui-Ting Huang, Kaisheng Yao, Dong Yu, Frank Seide, Michael Seltzer, Geoff Zweig, Xiaodong He, Jason Williams, et al. 2013 · 2013
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Efficient estimation of word representations in vector space
Tomas Mikolov, Kai Chen, Greg Corrado, and Jeffrey Dean. 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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Salient object detection: A survey
Ali Borji, Ming-Ming Cheng, Qibin Hou, Huaizu Jiang, and Jia Li. 2014 · 2014
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Explaining and harnessing adversarial examples
Ian J Goodfellow, Jonathon Shlens, and Christian Szegedy. 2014 · 2014
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An analysis of convolutional neural networks for speech recognition
Jui-Ting Huang, Jinyu Li, and Yifan Gong. 2015 · 2015
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Generating natural adversarial examples
Zhengli Zhao, Dheeru Dua, and Sameer Singh. 2017 · 2017
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Threat of adversarial attacks on deep learning in computer vision: A survey
Naveed Akhtar and Ajmal Mian. 2018 · 2018
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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 · 2018
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Matthias Blohm, Glorianna Jagfeld, Ekta Sood, Xiang Yu, and Ngoc Thang Vu. 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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Crafting adversarial input sequences for recurrent neural networks
Nicolas Papernot, Patrick McDaniel, Ananthram Swami, and Richard Harang. 2016 · 2016
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A boundary tilting persepective on the phenomenon of adversarial examples
Thomas Tanay and Lewis Griffin. 2016 · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 2016 · 2016
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Synthetic and natural noise both break neural machine translation
Yonatan Belinkov and Yonatan Bisk. 2017 · 2017
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Hotflip: White-box adversarial examples for text classification
Javid Ebrahimi, Anyi Rao, Daniel Lowd, and Dejing Dou. 2017 · 2017
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Adversarial examples for malware detection
Kathrin Grosse, Nicolas Papernot, Praveen Manoharan, Michael Backes, and Patrick McDaniel. 2017 · 2017
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Deceiving google’s perspective api built for detecting toxic comments
Hossein Hosseini, Sreeram Kannan, Baosen Zhang, and Radha Poovendran. 2017 · 2017
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On adversarial examples for character-level neural machine translation
Javid Ebrahimi, Daniel Lowd, and Dejing Dou. 2018 · 2018
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Black-box generation of adversarial text sequences to evade deep learning classifiers
Ji Gao, Jack Lanchantin, Mary Lou Soffa, and Yanjun Qi. 2018 · 2018
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Protecting voice controlled systems using sound source identification based on acoustic cues
Yuan Gong and Christian Poellabauer. 2018 · 2018
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Textbugger: Generating adversarial text against real-world applications
Jinfeng Li, Shouling Ji, Tianyu Du, Bo Li, and Ting Wang. 2018 · 2018
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Adversarial robustness toolbox v1.2.0
Maria-Irina Nicolae, Mathieu Sinn, Minh Ngoc Tran, Beat Buesser, Ambrish Rawat, Martin Wistuba, Valentina Zantedeschi, Nathalie Baracaldo, Bryant Chen, Heiko Ludwig, Ian Molloy, and Ben Edwards. 2018 · 2018
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Technical report on the cleverhans v2.1.0 adversarial examples library
Nicolas Papernot, Fartash Faghri, Nicholas Carlini, Ian Goodfellow, Reuben Feinman, Alexey Kurakin, Cihang Xie, Yash Sharma, Tom Brown, Aurko Roy, Alexander Matyasko, Vahid Behzadan, Karen Hambardzumyan, Zhishuai Zhang, Yi-Lin Juang, Zhi Li, Ryan Sheatsley, Abhibhav Garg, Jonathan Uesato, Willi Gierke, Yinpeng Dong, David Berthelot, Paul Hendricks, Jonas Rauber, and Rujun Long. 2018 · 2018
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Robust machine comprehension models via adversarial training
Yicheng Wang and Mohit Bansal. 2018 · 2018
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Deep learning for sentiment analysis: A survey
Lei Zhang, Shuai Wang, and Bing Liu. 2018 · 2018
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Analysis methods in neural language processing: A survey
Yonatan Belinkov and James Glass. 2019 · 2019
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Adversarial examples are not bugs, they are features
Andrew Ilyas, Shibani Santurkar, Dimitris Tsipras, Logan Engstrom, Brandon Tran, and Aleksander Madry. 2019 · 2019
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A survey of the usages of deep learning for natural language processing
Daniel W Otter, Julian R Medina, and Jugal K Kalita. 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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