4 papers
VagueBench: Benchmarking the Robustness of Embodied Agents on Ambient Context Illusions
Yang Qu, Qiang Fu, Zonghao Ying +7
Embodied agents are increasingly deployed in open-world environments, yet current robustness evaluations remain biased toward hazardous instructions and jailbreak vulnerabilities.…
LLM Detoxification via Transition-Aware Reward-Guided Representation Sampling
Aishan Liu, Yisong Xiao, Xianglong Liu +7
Large Language Models (LLMs) can generate toxic content, motivating effective test-time detoxification. Existing representation steering methods often rely on static or coarse inte…
Uncovering Security Threats and Architecting Defenses in Autonomous Agents: A Case Study of OpenClaw
Zonghao Ying, Xiao Yang, Siyang Wu +7
The rapid evolution of Large Language Models (LLMs) into autonomous, tool-calling agents has fundamentally altered the cybersecurity landscape. Frameworks like OpenClaw grant AI sy…
Black-Box Adversarial Attack on Vision Language Models for Autonomous Driving
Lu Wang, Tianyuan Zhang, Yang Qu +5
Vision-language models (VLMs) have significantly advanced autonomous driving (AD) by enhancing reasoning capabilities; however, these models remain highly susceptible to adversaria…