7 citations · 9 across the 9 of their papers we have counts for
9 papers
Which Changes Matter? Towards Trustworthy Legal AI via Relevance-Sensitive Evaluation and Solver-Grounded Reasoning
Chen Linze, Cai Yufan, Hou Zhe +1
Legal reasoning requires distinguishing changes that matter from those that do not. Legal AI should remain stable under legally irrelevant perturbations, but should change when per…
Uncertainty Reasoning with Large Language Models for Explainable Disease Diagnosis
Xiaoyang Fan, Yufan Cai, Zhe Hou +1
Clinical decision-making requires reasoning over incomplete, imprecise, and linguistically expressed patient narratives. While large language models (LLMs) excel at extracting late…
A Clinically Validated Foundation Model for Comprehensive Lung Pathology Interpretation
Zhengrui Guo, Zhengyu Zhang, Jiabo Ma +23
Pathological assessment guides lung cancer diagnosis, treatment selection, and prognostic evaluation, yet current CPath approaches rely on task-specific models for isolated objecti…
X-RAY: Mapping LLM Reasoning Capability via Formalized and Calibrated Probes
Tianxi Gao, Yufan Cai, Yusi Yuan +1
Large language models (LLMs) achieve promising performance, yet their ability to reason remains poorly understood. Existing evaluations largely emphasize task-level accuracy, often…
Towards Trustworthy Legal AI through LLM Agents and Formal Reasoning
Linze Chen, Yufan Cai, Zhe Hou +1
Legal decisions should be logical and based on statutory laws. While large language models(LLMs) are good at understanding legal text, they cannot provide verifiable justifications…
PAT-Agent: Autoformalization for Model Checking
Xinyue Zuo, Yifan Zhang, Hongshu Wang +4
Recent advances in large language models (LLMs) offer promising potential for automating formal methods. However, applying them to formal verification remains challenging due to th…
The Fusion of Large Language Models and Formal Methods for Trustworthy AI Agents: A Roadmap
Yedi Zhang, Yufan Cai, Xinyue Zuo +9
Large Language Models (LLMs) have emerged as a transformative AI paradigm, profoundly influencing daily life through their exceptional language understanding and contextual generat…
CoEdPilot: Recommending Code Edits with Learned Prior Edit Relevance, Project-wise Awareness, and Interactive Nature
Chenyan Liu, Yufan Cai, Yun Lin +6
Recent years have seen the development of LLM-based code generation. Compared to generating code in a software project, incremental code edits are empirically observed to be more f…
Towards Large Language Model Aided Program Refinement
Yufan Cai, Zhe Hou, Xiaokun Luan +4
Program refinement involves correctness-preserving transformations from formal high-level specification statements into executable programs. Traditional verification tool support f…