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pith:5QE347C6

pith:2026:5QE347C6EUITKRJ35EHQ2S7O4P
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Enjoy Your Layer Normalization with the Computational Efficiency of RMSNorm

Jie Luo, Lei Huang, Wenjun Wu, Yihao Yue, Yizhou Ruan, Yunhao Ni, Yuxin Guo

Many layer normalizations in standard networks can be folded exactly into upstream layers, allowing precise replacement by faster RMSNorm at inference time with no change in predictions.

arxiv:2605.14521 v1 · 2026-05-14 · cs.LG

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2 Internet Archive
3 Author claim open · sign in to claim
4 Citations open
5 Replications open
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Claims

C1strongest claim

Our analysis shows that many LNs in widely used architectures are foldable, enabling exact inference-time conversion and end-to-end acceleration of 2% to 12% without changing model predictions.

C2weakest assumption

That the column-centered constraint and column-based weight centering can be enforced on upstream linear layers without changing the overall model function or requiring major retraining adjustments.

C3one line summary

A framework to identify and convert foldable layer normalizations to RMSNorm for exact equivalence and faster inference in deep neural networks.

References

105 extracted · 105 resolved · 9 Pith anchors

[1] ICML , year =
[2] Contrastive multiview coding 1906
[3] Chun-Hsiao Yeh, Yubei Chen , howpublished=
[4] Proceedings of the IEEE/CVF International Conference on Computer Vision (ICCV) , year=
[5] Layer Normalization , author=. 2016 , eprint= 2016

Formal links

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First computed 2026-05-17T23:39:06.068337Z
Builder pith-number-builder-2026-05-17-v1
Signature Pith Ed25519 (pith-v1-2026-05) · public key
Schema pith-number/v1.0

Canonical hash

ec09be7c5e251135453be90f0d4beee3e58ac61c1287d651d24516862b9b63e3

Aliases

arxiv: 2605.14521 · arxiv_version: 2605.14521v1 · doi: 10.48550/arxiv.2605.14521 · pith_short_12: 5QE347C6EUIT · pith_short_16: 5QE347C6EUITKRJ3 · pith_short_8: 5QE347C6
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curl -sH 'Accept: application/ld+json' https://pith.science/pith/5QE347C6EUITKRJ35EHQ2S7O4P \
  | jq -c '.canonical_record' \
  | python3 -c "import sys,json,hashlib; b=json.dumps(json.loads(sys.stdin.read()), sort_keys=True, separators=(',',':'), ensure_ascii=False).encode(); print(hashlib.sha256(b).hexdigest())"
# expect: ec09be7c5e251135453be90f0d4beee3e58ac61c1287d651d24516862b9b63e3
Canonical record JSON
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