4 papers · 1 filter
EpiSEM-Bench: Evaluating Safety and Evidence Recovery in LLM Agents under Missing Evidence
Qijin Zhang, Hanzhen Wang, Yuehan Zhao +4
Tool-using language model agents rely on environmental facts to decide whether an action is permitted. When a tool response omits a safety-relevant fact, an agent may carry out a p…
Bridging Exploration and Persona: Information-Directed Dueling for Test-Time Agent Personalization
Jie Mao, Pingchen Lu, Xiangyi Wang +4
Effective test-time personalization requires LLM agents to adapt to query-dependent user preferences from lightweight interaction. We study persona selection with binary comparison…
Test-Time Scaling via Budgeted Multi-Attribute Verification
Bo Xue, Ji Cheng, Shen-Huan Lyu +2
Verifying LLM-generated answers under a shared computational budget requires jointly deciding which candidates to inspect and which verification attributes to evaluate. We formulat…
Learning to Reason with Insight for Informal Theorem Proving
Yunhe Li, Hao Shi, Bowen Deng +8
Although most of the automated theorem-proving approaches depend on formal proof systems, informal theorem proving can align better with large language models' (LLMs) strength in n…