1 citations · 1 across the 8 of their papers we have counts for
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Breaking Planner Integrity Boundary: Enviroment State-Text Injection Attack on LLM-Driven Embodied Agents
Jiawei Liu, Jiacheng Guo, Tian Zhang +7
Large language model (LLM)-driven embodied agents rely on environment states to interpret scenes, generate high-level plans, and drive physical execution, making planner-visible st…
Security of Foundation-Model-Powered Embodied Agents: Attack Surfaces, Attacks, Defenses, and Evaluation
Jiawei Liu, Jiacheng Guo, Tian Zhang +4
Foundation models are increasingly used for perception, reasoning, planning, and action generation in embodied agents, creating security risks that can propagate from digital input…
LLM agents security duality: a comprehensive survey of self-security and empowered cybersecurity
Yiwei Xu, Yong Zhuang, Xuanming Liu +6
Large language model (LLM) agents are rapidly being integrated into real-world systems. Their autonomy and tool-use capabilities generate substantial value while simultaneously exp…
Light-WAM: Efficient World Action Models with State-Fusion Action Decoding
Ziang Li, Dongzhou Cheng, Yibin Wang +5
World Action Models (WAMs) extend robot policy learning by incorporating future prediction as an additional training objective, encouraging the policy to encode task-relevant tempo…
AgentSentry: Mitigating Indirect Prompt Injection in LLM Agents via Temporal Causal Diagnostics and Context Purification
Tian Zhang, Yiwei Xu, Juan Wang +8
Tool-augmented large language model (LLM) agents aggregate dialogue history, tool outputs, and retrieved content into an accumulated runtime state to complete multi-step tasks. Thi…