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20232025
most citedSceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments

1 citations · 1 across the 4 of their papers we have counts for

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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★ 1 cited

SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments

Yue Cao, Yun Xing, Jie Zhang +5

Large vision-language models (LVLMs) have shown remarkable capabilities in interpreting visual content. While existing works demonstrate these models' vulnerability to deliberately…