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cs.CV2026
ClinFusion: A Vision-Centric Multimodal LLM System for Holistic Medical Understanding
Hangjie Yuan, Yichen Qian, Zhiwei Tang +21
Multimodal large language models (MLLMs) hold immense potential to revolutionize clinical practice, yet deploying them in the medical domain is fundamentally a vision-centric chall…
cs.CV2026
Chart-FR1: Visual Focus-Driven Fine-Grained Reasoning on Dense Charts
Hongkun Pan, Yuwei Wu, Wanyi Hong +8
Multimodal large language models (MLLMs) have shown considerable potential in chart understanding and reasoning tasks. However, they still struggle with high information density (H…
cs.CV2026
V-Zero: Self-Improving Multimodal Reasoning with Zero Annotation
Han Wang, Yi Yang, Jingyuan Hu +2
Recent advances in multimodal learning have significantly enhanced the reasoning capabilities of vision-language models (VLMs). However, state-of-the-art approaches rely heavily on…