ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation

22 October 2022

Papers citing "ADDMU: Detection of Far-Boundary Adversarial Examples with Data and Model Uncertainty Estimation"

25 / 25 papers shown

Title
"That Is a Suspicious Reaction!": Interpreting Logits Variation to Detect NLP Adversarial Attacks Edoardo Mosca Shreyash Agarwal Javier Rando Georg Groh AAML 90 31 0 10 Apr 2022
Identifying Adversarial Attacks on Text Classifiers Zhouhang Xie Jonathan Brophy Adam Noack Wencong You Kalyani Asthana Carter Perkins Sabrina Reis Sameer Singh Daniel Lowd AAML 82 9 0 21 Jan 2022
Detecting Textual Adversarial Examples through Randomized Substitution and Vote Xiaosen Wang Yifeng Xiong Kun He AAML 50 11 0 13 Sep 2021
Datasets: A Community Library for Natural Language Processing Quentin Lhoest Albert Villanova del Moral Yacine Jernite A. Thakur Patrick von Platen ... Thibault Goehringer Victor Mustar François Lagunas Alexander M. Rush Thomas Wolf 225 614 0 07 Sep 2021
Searching for an Effective Defender: Benchmarking Defense against Adversarial Word Substitution Zongyi Li Jianhan Xu Jiehang Zeng Linyang Li Xiaoqing Zheng Qi Zhang Kai-Wei Chang Cho-Jui Hsieh AAML 50 74 0 29 Aug 2021
Better Robustness by More Coverage: Adversarial Training with Mixup Augmentation for Robust Fine-tuning Chenglei Si Zhengyan Zhang Fanchao Qi Zhiyuan Liu Yasheng Wang Qun Liu Maosong Sun AAML SILM 92 69 0 31 Dec 2020
Defense against Adversarial Attacks in NLP via Dirichlet Neighborhood Ensemble Yi Zhou Xiaoqing Zheng Cho-Jui Hsieh Kai-Wei Chang Xuanjing Huang SILM 100 48 0 20 Jun 2020
Frequency-Guided Word Substitutions for Detecting Textual Adversarial Examples Maximilian Mozes Pontus Stenetorp Bennett Kleinberg Lewis D. Griffin AAML 172 103 0 13 Apr 2020
Robustness Verification for Transformers Zhouxing Shi Huan Zhang Kai-Wei Chang Minlie Huang Cho-Jui Hsieh AAML 81 109 0 16 Feb 2020
FreeLB: Enhanced Adversarial Training for Natural Language Understanding Chen Zhu Yu Cheng Zhe Gan S. Sun Tom Goldstein Jingjing Liu AAML 292 443 0 25 Sep 2019
Learning to Discriminate Perturbations for Blocking Adversarial Attacks in Text Classification Yichao Zhou Jyun-Yu Jiang Kai-Wei Chang Wei Wang AAML 63 119 0 06 Sep 2019
Certified Robustness to Adversarial Word Substitutions Robin Jia Aditi Raghunathan Kerem Göksel Percy Liang AAML 337 294 0 03 Sep 2019
Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment Di Jin Zhijing Jin Qiufeng Wang Peter Szolovits SILM AAML 204 1,090 0 27 Jul 2019
Combating Adversarial Misspellings with Robust Word Recognition Danish Pruthi Bhuwan Dhingra Zachary Chase Lipton 191 307 0 27 May 2019
TextBugger: Generating Adversarial Text Against Real-world Applications Jinfeng Li S. Ji Tianyu Du Bo Li Ting Wang SILM AAML 216 747 0 13 Dec 2018
A Simple Unified Framework for Detecting Out-of-Distribution Samples and Adversarial Attacks Kimin Lee Kibok Lee Honglak Lee Jinwoo Shin OODD 199 2,064 0 10 Jul 2018
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 417 933 0 21 Apr 2018
Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples Anish Athalye Nicholas Carlini D. Wagner AAML 249 3,195 0 01 Feb 2018
Characterizing Adversarial Subspaces Using Local Intrinsic Dimensionality Xingjun Ma Yue Liu Yisen Wang S. Erfani S. Wijewickrema Grant Schoenebeck Basel Alomair Michael E. Houle James Bailey AAML 120 742 0 08 Jan 2018
Towards Deep Learning Models Resistant to Adversarial Attacks Aleksander Madry Aleksandar Makelov Ludwig Schmidt Dimitris Tsipras Adrian Vladu SILM OOD 321 12,151 0 19 Jun 2017
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks Weilin Xu David Evans Yanjun Qi AAML 97 1,275 0 04 Apr 2017
Detecting Adversarial Samples from Artifacts Reuben Feinman Ryan R. Curtin S. Shintre Andrew B. Gardner AAML 109 894 0 01 Mar 2017
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 181 3,482 0 07 Oct 2016
A large annotated corpus for learning natural language inference Samuel R. Bowman Gabor Angeli Christopher Potts Christopher D. Manning 338 4,298 0 21 Aug 2015
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 899 9,364 0 06 Jun 2015