By systematically varying model size, training amount, and image type in DINOv3 vision transformers, this paper shows that brain similarity increases with scale and human-centric data and emerges in a characteristic training-time sequence.
Prince, George A
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Disentangling the Factors of Convergence between Brains and Computer Vision Models
By systematically varying model size, training amount, and image type in DINOv3 vision transformers, this paper shows that brain similarity increases with scale and human-centric data and emerges in a characteristic training-time sequence.