collaborators

5 papers

cs.CV2026

UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis

Junzhi Ning, Wei Li, Cheng Tang +24

Medical workflows routinely combine reading images with producing visual and textual outputs, making both image understanding and generation central to medical AI. Most existing sy…

cs.CV2026

MedProbeBench: Systematic Benchmarking at Deep Evidence Integration for Expert-level Medical Guideline

Jiyao Liu, Jianghan Shen, Sida Song +19

Recent advances in deep research systems enable large language models to retrieve, synthesize, and reason over large-scale external knowledge. In medicine, developing clinical guid…

cs.CV2025

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Weiyun Wang, Zhangwei Gao, Lixin Gu +72

We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…

cs.CV2025

GMAI-VL-R1: Harnessing Reinforcement Learning for Multimodal Medical Reasoning

Yanzhou Su, Tianbin Li, Jiyao Liu +15

Recent advances in general medical AI have made significant strides, but existing models often lack the reasoning capabilities needed for complex medical decision-making. This pape…

cs.CV2025

GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AI

Tianbin Li, Yanzhou Su, Wei Li +15

Despite significant advancements in general AI, its effectiveness in the medical domain is limited by the lack of specialized medical knowledge. To address this, we formulate GMAI-…