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cs.CV2024
MAGIC: Mastering Physical Adversarial Generation in Context through Collaborative LLM Agents
Yun Xing, Nhat Chung, Jie Zhang +5
Physical adversarial attacks in driving scenarios can expose critical vulnerabilities in visual perception models. However, developing such attacks remains challenging due to diver…
cs.CV2024
Towards Transferable Attacks Against Vision-LLMs in Autonomous Driving with Typography
Nhat Chung, Sensen Gao, Tuan-Anh Vu +5
Vision-Large-Language-Models (Vision-LLMs) are increasingly being integrated into autonomous driving (AD) systems due to their advanced visual-language reasoning capabilities, targ…