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20242026
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cs.CV2026

LUMEN: Longitudinal Multi-Modal Radiology Model for Prognosis and Diagnosis

Zhifan Jiang, Dong Yang, Vishwesh Nath +7

Large vision-language models (VLMs) have evolved from general-purpose applications to specialized use cases such as in the clinical domain, demonstrating potential for decision sup…

cs.CV2025

No Tokens Wasted: Leveraging Long Context in Biomedical Vision-Language Models

Min Woo Sun, Alejandro Lozano, Javier Gamazo Tejero +8

Embedding vision-language models (VLMs) are typically pretrained with short text windows (<77 tokens), which forces the truncation of long-format captions. Yet, the distribution of…

cs.CV2025

Unified Supervision For Vision-Language Modeling in 3D Computed Tomography

Hao-Chih Lee, Zelong Liu, Hamza Ahmed +6

General-purpose vision-language models (VLMs) have emerged as promising tools in radiology, offering zero-shot capabilities that mitigate the need for large labeled datasets. Howev…

cs.CV2024

NVILA: Efficient Frontier Visual Language Models

Zhijian Liu, Ligeng Zhu, Baifeng Shi +24

Visual language models (VLMs) have made significant advances in accuracy in recent years. However, their efficiency has received much less attention. This paper introduces NVILA, a…

cs.CV2024

VILA-M3: Enhancing Vision-Language Models with Medical Expert Knowledge

Vishwesh Nath, Wenqi Li, Dong Yang +22

Generalist vision language models (VLMs) have made significant strides in computer vision, but they fall short in specialized fields like healthcare, where expert knowledge is esse…