collaborators

6 papers

cs.CV2026

GlaKG: A Biomarker-Centric Fundus Knowledge Graph for Explainable Glaucoma Diagnosis and Risk Assessment

Cheng Huang, Jia Zhang, Yi Jiang +7

Glaucoma is a leading cause of irreversible blindness worldwide, yet most automated diagnosis systems rely on opaque deep-learning models that offer little clinical interpretabilit…

cs.AI2026

Deep reflective reasoning in interdependence constrained structured data extraction from clinical notes for digital health

Jingwei Huang, Kuroush Nezafati, Zhikai Chi +9

Extracting structured information from clinical notes requires navigating a dense web of interdependent variables where the value of one attribute logically constrains others. Exis…

cs.CV2026

MEDVISTAGYM: A Scalable Training Environment for Thinking with Medical Images via Tool-Integrated Reinforcement Learning

Meng Lu, Yuxing Lu, Yuchen Zhuang +6

Vision language models (VLMs) achieve strong performance on general image understanding but struggle to think with medical images, especially when performing multi-step reasoning t…

cs.AI2025

Scaling Agentic Reinforcement Learning for Tool-Integrated Reasoning in VLMs

Meng Lu, Ran Xu, Yi Fang +14

While recent vision-language models (VLMs) demonstrate strong image understanding, their ability to "think with images", i.e., to reason through multi-step visual interactions, rem…

cs.CL2025

MedAgentGym: A Scalable Agentic Training Environment for Code-Centric Reasoning in Biomedical Data Science

Ran Xu, Yuchen Zhuang, Yishan Zhong +13

We introduce MedAgentGym, a scalable and interactive training environment designed to enhance coding-based biomedical reasoning capabilities in large language model (LLM) agents. M…

cs.CV2025

GAS-MIL: Group-Aggregative Selection Multi-Instance Learning for Ensemble of Foundation Models in Digital Pathology Image Analysis

Peiran Quan, Zifan Gu, Zhuo Zhao +5

Foundation models (FMs) have transformed computational pathology by providing powerful, general-purpose feature extractors. However, adapting and benchmarking individual FMs for sp…