37 citations · 45 across the 4 of their papers we have counts for
4 papers
TCAB: A Large-Scale Text Classification Attack Benchmark
Kalyani Asthana, Zhouhang Xie, Wencong You +4
We introduce the Text Classification Attack Benchmark (TCAB), a dataset for analyzing, understanding, detecting, and labeling adversarial attacks against text classifiers. TCAB inc…
Identifying Adversarial Attacks on Text Classifiers
Zhouhang Xie, Jonathan Brophy, Adam Noack +6
The landscape of adversarial attacks against text classifiers continues to grow, with new attacks developed every year and many of them available in standard toolkits, such as Text…
An Empirical Study on the Relation between Network Interpretability and Adversarial Robustness
Adam Noack, Isaac Ahern, Dejing Dou +1
Deep neural networks (DNNs) have had many successes, but they suffer from two major issues: (1) a vulnerability to adversarial examples and (2) a tendency to elude human interpreta…
NormLime: A New Feature Importance Metric for Explaining Deep Neural Networks
Isaac Ahern, Adam Noack, Luis Guzman-Nateras +3
The problem of explaining deep learning models, and model predictions generally, has attracted intensive interest recently. Many successful approaches forgo global approximations i…