activity
20242026
most citedMDocAgent: A Multi-Modal Multi-Agent Framework for Document Understanding

4 citations · 5 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CV2026

Mitigating Batch Effects in Histopathology via Language-Mediated Robust Embedding Generation

Yishu Zhang, Shushan Wu, Zhenzhong Zhang +8

Pathology foundation models (PFMs) have demonstrated strong potential across clinical and scientific applications, yet their performance is often hindered by batch effects, which a…

cs.LG2025

MMedAgent-RL: Optimizing Multi-Agent Collaboration for Multimodal Medical Reasoning

Peng Xia, Jinglu Wang, Yibo Peng +10

Medical Large Vision-Language Models (Med-LVLMs) have shown strong potential in multimodal diagnostic tasks. However, existing single-agent models struggle to generalize across div…

cs.LG2025

MDocAgent: A Multi-Modal Multi-Agent Framework for Document Understanding

Siwei Han, Peng Xia, Ruiyi Zhang +4

Document Question Answering (DocQA) is a very common task. Existing methods using Large Language Models (LLMs) or Large Vision Language Models (LVLMs) and Retrieval Augmented Gener…

cs.CV2024

MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization

Kangyu Zhu, Peng Xia, Yun Li +3

The advancement of Large Vision-Language Models (LVLMs) has propelled their application in the medical field. However, Medical LVLMs (Med-LVLMs) encounter factuality challenges due…

cs.LG2024

RULE: Reliable Multimodal RAG for Factuality in Medical Vision Language Models

Peng Xia, Kangyu Zhu, Haoran Li +5

The recent emergence of Medical Large Vision Language Models (Med-LVLMs) has enhanced medical diagnosis. However, current Med-LVLMs frequently encounter factual issues, often gener…

cs.LG2024

CARES: A Comprehensive Benchmark of Trustworthiness in Medical Vision Language Models

Peng Xia, Ze Chen, Juanxi Tian +21

Artificial intelligence has significantly impacted medical applications, particularly with the advent of Medical Large Vision Language Models (Med-LVLMs), sparking optimism for the…