2 citations · 2 across the 6 of their papers we have counts for
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Which Tool Response Should I Trust? Tool-Expertise-Aware Chest X-ray Agent with Multimodal Agentic Learning
Zheang Huai, Honglong Yang, Xiaomeng Li
AI agents with tool-use capabilities show promise for integrating the domain expertise of various tools. In the medical field, however, tools are usually AI models that are inheren…
Proactive Reasoning-with-Retrieval Framework for Medical Multimodal Large Language Models
Lehan Wang, Yi Qin, Honglong Yang +1
Incentivizing the reasoning ability of Multimodal Large Language Models (MLLMs) is essential for medical applications to transparently analyze medical scans and provide reliable di…
Multi-Modal Explainable Medical AI Assistant for Trustworthy Human-AI Collaboration
Honglong Yang, Shanshan Song, Yi Qin +6
Generalist Medical AI (GMAI) systems have demonstrated expert-level performance in biomedical perception tasks, yet their clinical utility remains limited by inadequate multi-modal…
DDaTR: Dynamic Difference-aware Temporal Residual Network for Longitudinal Radiology Report Generation
Shanshan Song, Hui Tang, Honglong Yang +1
Radiology Report Generation (RRG) automates the creation of radiology reports from medical imaging, enhancing the efficiency of the reporting process. Longitudinal Radiology Report…
Interpretable Bilingual Multimodal Large Language Model for Diverse Biomedical Tasks
Lehan Wang, Haonan Wang, Honglong Yang +4
Several medical Multimodal Large Languange Models (MLLMs) have been developed to address tasks involving visual images with textual instructions across various medical modalities,…
FITA: Fine-grained Image-Text Aligner for Radiology Report Generation
Honglong Yang, Hui Tang, Xiaomeng Li
Radiology report generation aims to automatically generate detailed and coherent descriptive reports alongside radiology images. Previous work mainly focused on refining fine-grain…