3 papers
cs.CL2025
Overcoming Black-box Attack Inefficiency with Hybrid and Dynamic Select Algorithms
Abhinay Shankar Belde, Rohit Ramkumar, Jonathan Rusert
Adversarial text attack research plays a crucial role in evaluating the robustness of NLP models. However, the increasing complexity of transformer-based architectures has dramatic…
cs.CL2025
RedHerring Attack: Testing the Reliability of Attack Detection
Jonathan Rusert
In response to adversarial text attacks, attack detection models have been proposed and shown to successfully identify text modified by adversaries. Attack detection models can be…
cs.CR2024
BinarySelect to Improve Accessibility of Black-Box Attack Research
Shatarupa Ghosh, Jonathan Rusert
Adversarial text attack research is useful for testing the robustness of NLP models, however, the rise of transformers has greatly increased the time required to test attacks. Espe…