no code implementations • 28 Feb 2024 • Zhuoer Xu, Jianping Zhang, Shiwen Cui, Changhua Meng, Weiqiang Wang
Not only are these methods labor-intensive and require large budget costs, but the controllability of test prompt generation is lacking for the specific testing domain of LLM applications.
no code implementations • ICCV 2023 • Zhuoer Xu, Zhangxuan Gu, Jianping Zhang, Shiwen Cui, Changhua Meng, Weiqiang Wang
Transfer-based attackers craft adversarial examples against surrogate models and transfer them to victim models deployed in the black-box situation.
1 code implementation • 14 Jun 2023 • Jianping Zhang, Zhuoer Xu, Shiwen Cui, Changhua Meng, Weibin Wu, Michael R. Lyu
Therefore, in this paper, we aim to analyze the robustness of latent diffusion models more thoroughly.
1 code implementation • 7 Oct 2022 • Zhuoer Xu, Guanghui Zhu, Changhua Meng, Shiwen Cui, ZhenZhe Ying, Weiqiang Wang, Ming Gu, Yihua Huang
In this paper, we propose an efficient automated attacker called A2 to boost AT by generating the optimal perturbations on-the-fly during training.