5 citations · 9 across the 6 of their papers we have counts for
6 papers
PoInit-of-View: Poisoning Initialization of Views Transfers Across Multiple 3D Reconstruction Systems
Weijie Wang, Songlong Xing, Zhengyu Zhao +2
Poisoning input views of 3D reconstruction systems has been recently studied. However, we identify that existing studies simply backpropagate adversarial gradients through the 3D r…
Finetune Like You Pretrain: Boosting Zero-shot Adversarial Robustness in Vision-language Models
Songlong Xing, Weijie Wang, Zhengyu Zhao +3
Despite their impressive zero-shot abilities, vision-language models such as CLIP have been shown to be susceptible to adversarial attacks. To enhance its adversarial robustness, r…
When Safe Concepts Become Unsafe: Multi-Concept Compositional Vulnerabilities in Text-to-Image Models
Chaoshuo Zhang, Yibo Liang, Mengke Tian +7
Text-to-image (T2I) models are increasingly optimized for following user instructions faithfully. However, we find that this capability introduces a safety vulnerability we call Mu…
Prompt Backdoors in Visual Prompt Learning
Hai Huang, Zhengyu Zhao, Michael Backes +2
Fine-tuning large pre-trained computer vision models is infeasible for resource-limited users. Visual prompt learning (VPL) has thus emerged to provide an efficient and flexible al…
Revisiting Transferable Adversarial Images: Systemization, Evaluation, and New Insights
Zhengyu Zhao, Hanwei Zhang, Renjue Li +6
Transferable adversarial images raise critical security concerns for computer vision systems in real-world, black-box attack scenarios. Although many transfer attacks have been pro…
Composite Backdoor Attacks Against Large Language Models
Hai Huang, Zhengyu Zhao, Michael Backes +2
Large language models (LLMs) have demonstrated superior performance compared to previous methods on various tasks, and often serve as the foundation models for many researches and…