collaborators

7 papers

cs.RO2026

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…

cs.RO2026

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…

cs.CR2026

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…

cs.LG2026

Efficient Hyperparameter Optimization for LLM Reinforcement Learning

Minping Chen, Bowen Xiao, Du Liang +2

Reinforcement learning (RL) for large language models (LLMs) is highly sensitive to hyperparameter configurations, making hyperparameter optimization (HPO) essential yet computatio…

cs.CR2026

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…

cs.LG2025

Virtual Width Networks

Seed, Baisheng Li, Banggu Wu +115

We introduce Virtual Width Networks (VWN), a framework that delivers the benefits of wider representations without incurring the quadratic cost of increasing the hidden size. VWN d…

cs.DC2025

LiquidGEMM: Hardware-Efficient W4A8 GEMM Kernel for High-Performance LLM Serving

Huanqi Hu, Bowen Xiao, Shixuan Sun +8

Quantization is a critical technique for accelerating LLM inference by reducing memory footprint and improving computational efficiency. Among various schemes, 4-bit weight and 8-b…