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cs.CV2026
MedPMC: A Systematic Framework for Scaling High-Fidelity Medical Multimodal Data for Foundation Models
Hyunjae Kim, Dain Kim, Pan Xiao +25
Medicine is inherently multimodal, requiring clinicians to synthesize information across diverse data streams. Yet the development of multimodal foundation models is constrained by…
cs.CV2026
Are Multimodal LLMs Ready for Clinical Dermatology? A Real-World Evaluation in Dermatology
Roy Jiang, Hyunjae Kim, Zhenyue Qin +8
Multimodal large language models (MLLMs) have demonstrated promise on publicly available dermatology benchmarks. However, benchmark performance may not generalize to real-world der…
cs.CV2025
From Compound Figures to Medical Multi-image Reasoning: Scaling Multimodal Large Language Models with Biomedical Literature
Zhen Chen, Yihang Fu, Rong Zhou +12
Multimodal large language models (MLLMs) are increasingly capable in medical imaging, yet most focus on single-image settings. Clinical interpretation often requires integrating ev…