9 papers
SymDiag: Explainable Diagnosis for LLM Reasoning via Neuro-Symbolic Verification
Wenyao Cui, Huaping Zhang, Yongyi Huang +6
Large language models (LLMs) increasingly serve as data-driven reasoners, yet their chains-of-thought (CoT) can be unfaithful even when final answers are correct. Most existing ``v…
Grounding Multi-Hop Reasoning in Structural Causal Models via Group Relative Policy Optimization
Yunhan Bu, Quan Zhang, Huaping Zhang +9
Multi-Hop Fact Verification requires complex reasoning across disparate evidence, posing significant challenges for Large Language Models , which may suffer from hallucinations and…
Improving Multimodal Reasoning via Worst Dimension Optimization
Haocheng Lv, Huaping Zhang, Qiuchi Li +2
Multimodal reasoning requires a path that retains integrity over a wide range of constraints, from visual grounding to logic consistency. However, the current Process Reward Models…
BadgeX: IoT-Enhanced Wearable Analytics Meets LLMs for Collaborative Learning
Zaibei Li, Shunpei Yamaguchi, Qiuchi Li +1
We present BadgeX, a novel system integrating lightweight wearable IoT devices (smart badges/smartphones) with Large Language Models (LLMs) to enable real-time collaborative learni…
NurValues: Real-World Nursing Values Evaluation for Large Language Models in Clinical Context
Ben Yao, Qiuchi Li, Yazhou Zhang +4
While LLMs have demonstrated medical knowledge and conversational ability, their deployment in clinical practice raises new risks: patients may place greater trust in LLM-generated…
Visual Room 2.0: Seeing is Not Understanding for MLLMs
Haokun Li, Yazhou Zhang, Jizhi Ding +2
Can multi-modal large language models (MLLMs) truly understand what they can see? Extending Searle's Chinese Room into the multi-modal domain, this paper proposes the Visual Room a…