collaborators

5 papers

cs.AI2026

Volumetric Radiology AI in the Era of Multimodal Large Language Models

Zanting Ye, Shengyuan Liu, Xin Liu +16

Advances in multimodal large language models (MLLMs) are extending radiological artificial intelligence (AI) beyond task-specific image analysis toward multimodal understanding and…

cs.CV2026

Open-Linguistic Concept Unified Learning for Cross-Site Interpretable Dermatology Image Diagnosis

Chengyu Wu, Junpeng Tan, Wanxiang Luo +3

Human-interpretable computer-aided diagnosis is crucial for clinical decision making. Concept-based models excel by providing transparent reasoning and enabling post-hoc, clinician…

cs.CV2026

InViC: Intent-aware Visual Cues for Medical Visual Question Answering

Zhisong Wang, Ziyang Chen, Zanting Ye +3

Medical visual question answering (Med-VQA) aims to answer clinically relevant questions grounded in medical images. However, existing multimodal large language models (MLLMs) ofte…

cs.CV2026

Step-CoT: Stepwise Visual Chain-of-Thought for Medical Visual Question Answering

Lin Fan, Yafei Ou, Zhipeng Deng +8

Chain-of-thought (CoT) reasoning has advanced medical visual question answering (VQA), yet most existing CoT rationales are free-form and fail to capture the structured reasoning p…

cs.AI2026

Evolving Medical Imaging Agents via Experience-driven Self-skill Discovery

Lin Fan, Pengyu Dai, Zhipeng Deng +4

Clinical image interpretation is inherently multi-step and tool-centric: clinicians iteratively combine visual evidence with patient context, quantify findings, and refine their de…