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Certified Multi-Turn Robustness for LLM Safety via Compositional Bounds and Safety Persistence
Yang Liu, Bin Chong, Wenkai Yang +9
Large language models (LLMs) are vulnerable to multi-turn jailbreak attacks that progressively manipulate conversation context. Existing certified robustness methods are limited to…
MemArbiter: Decision-Time Memory Arbitration for Long-Horizon LLM Agents
Jiajun Dong, Yutao Hu, Fengrui Fan +3
Large language model (LLM) agents must retain and use cross-step information to act coherently in long-horizon tasks. Existing methods improve memory accessibility, yet action-rele…
PlanningBench: Generating Scalable and Verifiable Planning Data for Evaluating and Training Large Language Models
Ziliang Zhao, Zenan Xu, Shuting Wang +7
Planning is a fundamental capability for large language models (LLMs) because such complex tasks require models to coordinate goals, constraints, resources, and long-term consequen…
Towards Security-Auditable LLM Agents: A Unified Graph Representation
Chaofan Li, Lyuye Zhang, Jintao Zhai +9
LLM-based agentic systems are rapidly evolving to perform complex autonomous tasks through dynamic tool invocation, stateful memory management, and multi-agent collaboration. Howev…
JFTA-Bench: Evaluate LLM's Ability of Tracking and Analyzing Malfunctions Using Fault Trees
Yuhui Wang, Zhixiong Yang, Ming Zhang +10
In the maintenance of complex systems, fault trees are used to locate problems and provide targeted solutions. To enable fault trees stored as images to be directly processed by la…
Steering LLMs via Scalable Interactive Oversight
Enyu Zhou, Zhiheng Xi, Long Ma +9
As Large Language Models increasingly automate complex, long-horizon tasks such as \emph{vibe coding}, a supervision gap has emerged. While models excel at execution, users often s…