Unverified50% confidenceFactExact time
CLIP使用InfoNCE损失（基于softmax的对比损失），原始训练使用了高达32768的批量大小
1
Sources
50%
Confidence
Long-term
Relevance
7/10/2026
First Seen
Sources
DINOv2 vs SigLIP: Why the Huge Gap in k-NN Classification? A Guide to Avoiding Vision Encoder Selection Pitfalls
redditr/MachineLearning7/8/2026
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