11 citations · 29 across the 14 of their papers we have counts for
5 papers · 1 filter
Is the Future Predictable? Modeling Future Predictability for Reliable Temporal Reasoning
Yongyi Huang, Huaping Zhang, Wenyao Cui +3
Large language models (LLMs) remain unreliable when reasoning about the future. Existing models often overlook the difference among future states, committing to specific answers ev…
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…