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20232026
most citedSA-Med2D-20M Dataset: Segment Anything in 2D Medical Imaging with 20 Million masks

14 citations · 43 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.CV2026

Towards Physics-Faithful Generation of Scientific Diagrams

Minghui Zhang, Jinxin Shi, Yifan Chang +12

Text-to-image generation has reached photorealistic quality, yet state-of-the-art systems remain unreliable at producing scientific diagrams, whose value depends not on appearance…

cs.CV2025★ 4 cited

InternVL3.5: Advancing Open-Source Multimodal Models in Versatility, Reasoning, and Efficiency

Weiyun Wang, Zhangwei Gao, Lixin Gu +72

We introduce InternVL 3.5, a new family of open-source multimodal models that significantly advances versatility, reasoning capability, and inference efficiency along the InternVL…

cs.CV2024★ 1 cited

GMAI-VL & GMAI-VL-5.5M: A Large Vision-Language Model and A Comprehensive Multimodal Dataset Towards General Medical AI

Tianbin Li, Yanzhou Su, Wei Li +15

Despite significant advancements in general AI, its effectiveness in the medical domain is limited by the lack of specialized medical knowledge. To address this, we formulate GMAI-…

cs.CV2024★ 1 cited

SlideChat: A Large Vision-Language Assistant for Whole-Slide Pathology Image Understanding

Ying Chen, Guoan Wang, Yuanfeng Ji +7

Despite the progress made by multimodal large language models (MLLMs) in computational pathology, they remain limited by a predominant focus on patch-level analysis, missing essent…

cs.CV2023★ 2 cited

Towards the Unification of Generative and Discriminative Visual Foundation Model: A Survey

Xu Liu, Tong Zhou, Yuanxin Wang +7

The advent of foundation models, which are pre-trained on vast datasets, has ushered in a new era of computer vision, characterized by their robustness and remarkable zero-shot gen…

cs.CV2023★ 11 cited

SAM-Med3D: Towards General-purpose Segmentation Models for Volumetric Medical Images

Haoyu Wang, Sizheng Guo, Jin Ye +11

Existing volumetric medical image segmentation models are typically task-specific, excelling at specific target but struggling to generalize across anatomical structures or modalit…