Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks

21 May 2021

Papers citing "Exploring Misclassifications of Robust Neural Networks to Enhance Adversarial Attacks"

6 / 6 papers shown

Title
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors Shuangpeng Han Mengmi Zhang 78 0 0 03 Oct 2024
Soft Prompt Threats: Attacking Safety Alignment and Unlearning in Open-Source LLMs through the Embedding Space Leo Schwinn David Dobre Sophie Xhonneux Gauthier Gidel Stephan Gunnemann AAML 47 36 0 14 Feb 2024
Raising the Bar for Certified Adversarial Robustness with Diffusion Models Thomas Altstidl David Dobre Björn Eskofier Gauthier Gidel Leo Schwinn DiffM 25 7 0 17 May 2023
Robust Smart Home Face Recognition under Starving Federated Data Jaechul Roh Yajun Fang FedML CVBM AAML 19 0 0 10 Nov 2022
Measure and Improve Robustness in NLP Models: A Survey Xuezhi Wang Haohan Wang Diyi Yang 139 130 0 15 Dec 2021
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 217 674 0 19 Oct 2020