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Dual PatchNorm

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arxiv 2302.01327 v3 pith:P2QCOYP6 submitted 2023-02-02 cs.CV cs.LG

Manoj Kumar , Mostafa Dehghani , Neil Houlsby This is my paper · ORCID
classification cs.CVcs.LG
keywords dualpatchnormlayertransformersvisionaccuracyalternativebefore
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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, incorporating this trivial modification, often leads to improved accuracy over well-tuned Vision Transformers and never hurts.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. V-Simba: Unleashing the Architectural Potential of RL in Visual Continuous Control

    cs.LG 2026-08 conditional novelty 6.0 of 10

    V-Simba, a visual RL architecture combining layer normalization, weight decay, and a distributional critic, matches or outperforms complex baselines on 29 continuous control tasks while using less compute.

  2. Reinforcement Learning: From Algorithms To Foundation Models

    cs.AI 2026-07 conditional novelty 3.0 of 10

    A dissertation uniting the author's published results: non-exploitable Nash-DQN policies and the FightLadder benchmark for games, plus diffusion/consistency-model world models for RL — a compilation rather than new results.

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