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cs.AI2026
NEXUS: Learning Safety Constraints and Action Models for Safe and Robust Embodied Planning
Tiehan Cui, Peipei Liu, Yanxu Mao +4
Large language models (LLMs) enable embodied agents to plan from naturallanguage instructions, yet their actions may be physically infeasible or hazardous. Existing neuro-symbolic…
cs.CL2026
Stop Fixating on Prompts: Reasoning Hijacking and Constraint Tightening for Red-Teaming LLM Agents
Yanxu Mao, Peipei Liu, Tiehan Cui +3
With the widespread application of LLM-based agents across various domains, their complexity has introduced new security threats. Existing red-team methods mostly rely on modifying…
cs.AI2026
ProtRLSearch: A Multi-Round Multimodal Protein Search Agent with Large Language Models Trained via Reinforcement Learning
Congying Liu, Taihao Li, Ming Huang +5
Protein analysis tasks arising in healthcare settings often require accurate reasoning under protein sequence constraints, involving tasks such as functional interpretation of dise…