Arrow Research search
Back to TMLR

TMLR 2023

Dual PatchNorm

Journal Article Articles Artificial Intelligence ยท Machine Learning

Abstract

We propose Dual PatchNorm: two Layer Normalization layers (LayerNorms), before and after the patch embedding layer in Vision Transformers. We demonstrate that Dual PatchNorm outperforms the result of exhaustive search for alternative LayerNorm placement strategies in the Transformer block itself. In our experiments on image classification and contrastive learning, incorporating this trivial modification, often leads to improved accuracy over well-tuned vanilla Vision Transformers and never hurts.

Authors

Keywords

No keywords are indexed for this paper.

Context

Venue
Transactions on Machine Learning Research
Archive span
2022-2026
Indexed papers
3849
Paper id
311274513419195915
v2026.09.13