activity
20232026
most citedA ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis

14 citations · 17 across the 7 of their papers we have counts for

collaborators

8 papers

cs.CL2026

MedUAG: Unified Understanding and Generation for Medical Multimodal Models

Zijie Meng, Yuncheng Zhang, Hualiang Wang +8

Recent Multimodal Large Language Models (MLLMs) are rapidly evolving into unified understanding and generation (UAG) frameworks. However, extending these unified paradigms to the m…

cs.CV2026

Wan-Weaver: Interleaved Multi-modal Generation via Decoupled Training

Jinbo Xing, Zeyinzi Jiang, Yuxiang Tuo +15

Recent unified models have made unprecedented progress in both understanding and generation. However, while most of them accept multi-modal inputs, they typically produce only sing…

cs.CV2025★ 1 cited

DentVLM: A Multimodal Vision-Language Model for Comprehensive Dental Diagnosis and Enhanced Clinical Practice

Zijie Meng, Jin Hao, Xiwei Dai +20

Diagnosing and managing oral diseases necessitate advanced visual interpretation across diverse imaging modalities and integrated information synthesis. While current AI models exc…

cs.CE2025

V2T-CoT: From Vision to Text Chain-of-Thought for Medical Reasoning and Diagnosis

Yuan Wang, Jiaxiang Liu, Shujian Gao +5

Recent advances in multimodal techniques have led to significant progress in Medical Visual Question Answering (Med-VQA). However, most existing models focus on global image featur…

cs.CV2025

3D-RAD: A Comprehensive 3D Radiology Med-VQA Dataset with Multi-Temporal Analysis and Diverse Diagnostic Tasks

Xiaotang Gai, Jiaxiang Liu, Yichen Li +3

Medical Visual Question Answering (Med-VQA) holds significant potential for clinical decision support, yet existing efforts primarily focus on 2D imaging with limited task diversit…

cs.CL2025

FairSteer: Inference Time Debiasing for LLMs with Dynamic Activation Steering

Yichen Li, Zhiting Fan, Ruizhe Chen +4

Large language models (LLMs) are prone to capturing biases from training corpus, leading to potential negative social impacts. Existing prompt-based debiasing methods exhibit insta…

cs.CV2024★ 2 cited

MedThink: Explaining Medical Visual Question Answering via Multimodal Decision-Making Rationale

Xiaotang Gai, Chenyi Zhou, Jiaxiang Liu +3

Medical Visual Question Answering (MedVQA), which offers language responses to image-based medical inquiries, represents a challenging task and significant advancement in healthcar…

eess.IV2023★ 14 cited

A ChatGPT Aided Explainable Framework for Zero-Shot Medical Image Diagnosis

Jiaxiang Liu, Tianxiang Hu, Yan Zhang +3

Zero-shot medical image classification is a critical process in real-world scenarios where we have limited access to all possible diseases or large-scale annotated data. It involve…