13 citations · 19 across the 10 of their papers we have counts for
6 papers · 1 filter
Authorization Closure Graph: Minimal Repair for LLM Agents with Evolving User Instructions
Qingzhuo Wang, CaiYi Wang, Jinglu Meng +4
Tool-using large language model (LLM) agents increasingly perform state-changing actions that require user authorization. Yet existing approaches do not provide a principled mechan…
Evaluating and Explaining Prompt Sensitivity of LLMs Using Interactions
Ruiyang Qin, Qingzhuo Wang, Tian Wang +2
The remarkable capabilities of large language models (LLMs) are often undermined by their instability. Even subtle and semantically irrelevant changes in prompts can cause dramatic…
A Unified Approach to Interpreting Knowledge Distillation for Large Language Models via Interactions
Qingzhuo Wang, Ruiyang Qin, Zhenxin Qin +2
Despite the success of knowledge distillation (KD) in Large Language Models (LLMs), the underlying mechanism behind its efficacy remains unclear. In this paper, we propose a unifie…
Mitigating Action-Relation Hallucinations in LVLMs via Relation-aware Visual Enhancement
Zhenxin Qin, Qiang Li, Qingzhuo Wang +3
Large Vision-Language Models (LVLMs) have achieved remarkable performance on diverse vision-language tasks. However, LVLMs still suffer from hallucinations, generating text that co…
Multilingual Safety Alignment via Self-Distillation
Ruiyang Qin, Qingzhuo Wang, Dongrui Liu +3
Large language models (LLMs) exhibit severe multilingual safety misalignment: they possess strong safeguards in high-resource languages but remain highly vulnerable to jailbreak at…
TME-PSR: Time-aware, Multi-interest, and Explanation Personalization for Sequential Recommendation
Qingzhuo Wang, Leilei Wen, Juntao Chen +4
In this paper, we propose a sequential recommendation model that integrates Time-aware personalization, Multi-interest personalization, and Explanation personalization for Personal…