no code implementations • 1 Jan 2024 • Wenxuan Wang, Juluan Shi, Zhaopeng Tu, Youliang Yuan, Jen-tse Huang, Wenxiang Jiao, Michael R. Lyu
Current methods for evaluating LLMs' veracity are limited by test data leakage or the need for extensive human labor, hindering efficient and accurate error detection.
no code implementations • 31 Oct 2023 • Kunyu Wang, Juluan Shi, Wenxuan Wang
In this work, we present a novel approach to generate transferable targeted adversarial examples by exploiting the vulnerability of deep neural networks to perturbations on high-frequency components of images.