Detecting Textual Adversarial Examples Based on Distributional
Characteristics of Data Representations

Detecting Textual Adversarial Examples Based on Distributional Characteristics of Data Representations

29 April 2022

Mark Dras

Wei Emma Zhang

Papers citing "Detecting Textual Adversarial Examples Based on Distributional Characteristics of Data Representations"

7 / 7 papers shown

Title
What Learned Representations and Influence Functions Can Tell Us About Adversarial Examples Shakila Mahjabin Tonni Mark Dras TDI AAML GAN 16 0 0 19 Sep 2023
On the Universal Adversarial Perturbations for Efficient Data-free Adversarial Detection Songyang Gao Shihan Dou Qi Zhang Xuanjing Huang Jin Ma Yingchun Shan AAML 9 3 0 27 Jun 2023
Robust Encodings: A Framework for Combating Adversarial Typos Erik Jones Robin Jia Aditi Raghunathan Percy Liang AAML 134 102 0 04 May 2020
Certified Robustness to Adversarial Word Substitutions Robin Jia Aditi Raghunathan Kerem Göksel Percy Liang AAML 183 290 0 03 Sep 2019
Generating Natural Language Adversarial Examples M. Alzantot Yash Sharma Ahmed Elgohary Bo-Jhang Ho Mani B. Srivastava Kai-Wei Chang AAML 245 914 0 21 Apr 2018
Adversarial Example Generation with Syntactically Controlled Paraphrase Networks Mohit Iyyer John Wieting Kevin Gimpel Luke Zettlemoyer AAML GAN 196 711 0 17 Apr 2018
Learning Robust Representations of Text Yitong Li Trevor Cohn Timothy Baldwin OOD 154 15 0 20 Sep 2016