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arXiv 提交日期: 2026-01-24
📄 Abstract - C-RADIOv4 (Tech Report)

By leveraging multi-teacher distillation, agglomerative vision backbones provide a unified student model that retains and improves the distinct capabilities of multiple teachers. In this tech report, we describe the most recent release of the C-RADIO family of models, C-RADIOv4, which builds upon AM-RADIO/RADIOv2.5 in design, offering strong improvements on key downstream tasks at the same computational complexity. We release -SO400M (412M params), and -H (631M) model variants, both trained with an updated set of teachers: SigLIP2, DINOv3, and SAM3. In addition to improvements on core metrics and new capabilities from imitating SAM3, the C-RADIOv4 model family further improves any-resolution support, brings back the ViTDet option for drastically enhanced efficiency at high-resolution, and comes with a permissive license.

顶级标签: computer vision model training multi-modal
详细标签: vision backbone knowledge distillation multi-teacher learning any-resolution vitdet 或 搜索:

C-RADIOv4 技术报告 / C-RADIOv4 (Tech Report)


1️⃣ 一句话总结

这篇技术报告介绍了C-RADIOv4模型,它通过整合多个先进教师模型的优势,在保持计算量不变的前提下,显著提升了多种视觉任务(如图像理解、分割)的性能,并新增了支持任意分辨率、高效高分辨率处理等实用功能。

源自 arXiv: 2601.17237