23 papers
Learning User-Aware Recall: Personalized Retrieval in Long-Term Conversational Memory
ZhiShu Jiang, Haibo Liu, Xin Shen +6
Long-term conversational agents are expected to remember past interactions, but memory is useful only when the right evidence is recalled for the right user. Existing memory-augmen…
Break the Brake, Not the Wheel: Untargeted Jailbreak via Entropy Maximization
Mengqi He, Xinyu Tian, Xin Shen +6
Recent studies show that gradient-based universal image jailbreaks on vision-language models (VLMs) exhibit little or no cross-model transferability, casting doubt on the feasibili…
ActTraitBench: Quantifying the Knowledge-Decision Gap in Large Language Models via Human-Grounded Behavioral Validation
Yutong Yang, Chenxi Miao, Weikang Li +1
While Large Language Models (LLMs) can convincingly simulate personas in explicit self-reports, they often deviate in implicit behavioral decisions, revealing a substantial Knowled…
Woodpecker Distillation: Weak Models Diagnose Reasoning Bugs in Strong Models
Dayu Wang, Jiaye Yang, Weikang Li +4
Large language models often fail on reasoning tasks despite possessing the capability to solve them. We argue that many such failures arise from localized reasoning bugs in interme…
Trait-Aware Policy Optimization for Autoregressive Multi-Trait Essay Scoring
Zhengyang Wang, Sanwoo Lee, Jiaxin Wang +3
Multi-trait essay scoring aims to provide fine-grained evaluation of writing quality across multiple dimensions. However, how to effectively post-train autoregressive scoring model…
One Tool Is Enough: Reinforcement Learning for Repository-Level LLM Agents
Zhaoxi Zhang, Yitong Duan, Yanzhi Zhang +9
Locating files and functions requiring modification in large software repositories is challenging due to their scale and structural complexity. Existing LLM-based methods typically…