AI RESEARCH

Attention Transfer Is Not Universally Effective for Vision Transformers

arXiv CS.LG

ArXi:2605.07191v1 Announce Type: cross A recent work shows that Attention Transfer, which transfers only the attention patterns from a pre-trained teacher Vision Transformer (ViT) to a randomly initialized standard student ViT, is sufficient to recover the full benefit of the teacher's pre-trained weights. We revisit this finding on a comprehensive benchmark of 20 teachers from 11 well-known ViT families and reveal that Attention Transfer is not universally effective.