4 papers
A Sentence Relation-Based Approach to Sanitizing Malicious Instructions
Soumil Datta, Melissa Umble, Daniel S. Brown +1
Retrieval-augmented generation and tool-integrated LLM agents increasingly depend on external textual sources. This reliance broadens the available attack surface, allowing adversa…
Less Is More -- Until It Breaks: Security Pitfalls of Vision Token Compression in Large Vision-Language Models
Xiaomei Zhang, Zhaoxi Zhang, Leo Yu Zhang +3
Visual token compression is widely adopted to improve the inference efficiency of Large Vision-Language Models (LVLMs), enabling their deployment in latency-sensitive and resource-…
Backdoor Attack on Vision Language Models with Stealthy Semantic Manipulation
Zhiyuan Zhong, Zhen Sun, Yepang Liu +2
Vision Language Models (VLMs) have shown remarkable performance, but are also vulnerable to backdoor attacks whereby the adversary can manipulate the model's outputs through hidden…
How Vulnerable Is My Learned Policy? Universal Adversarial Perturbation Attacks On Modern Behavior Cloning Policies
Akansha Kalra, Basavasagar Patil, Guanhong Tao +1
Learning from demonstrations is a popular approach to train AI models; however, their vulnerability to adversarial attacks remains underexplored. We present the first systematic st…