Paper Citation Record · LEDGER

Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 10 inbound Pith citation observations for arXiv:2502.02732.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2502.02732 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 10 of 10 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 10 of 10 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:21:10.661789Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-04T20:30:07.740339Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5ed40db9-0ac8-49d2-9536-daa3fb9bbafe · inbound

GPAS: Accelerating Convergence of LLM Pretraining via Gradient-Preserving Activation Scaling cites this paper.

GPAS: Accelerating Convergence of LLM Pretraining via Gradient-Preserving Activation Scaling Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-06T22:21:10.661789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 06bcf884-d9c7-4e6d-947d-a84f125f271c · inbound

SpanNorm: Reconciling Training Stability and Performance in Deep Transformers cites this paper.

SpanNorm: Reconciling Training Stability and Performance in Deep Transformers Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T06:37:52.586372Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b04c715f-4d2d-4480-a55f-e04f410edc69 · inbound

LoRDO: Distributed Low-Rank Optimization with Infrequent Communication cites this paper.

LoRDO: Distributed Low-Rank Optimization with Infrequent Communication Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-03T04:44:55.564583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a43618bd-4db6-4598-b4fb-d7af19f0727e · inbound

SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm cites this paper.

SiameseNorm: Breaking the Barrier to Reconciling Pre/Post-Norm Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-05-22T11:14:47.951414Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 78dcf9be-8b7a-4367-933a-18d8627f13ed · inbound

Stability and Generalization in Looped Transformers cites this paper.

Stability and Generalization in Looped Transformers Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 14

Resolution: verified exact; arxiv_id, observed 2026-05-10T12:25:22.716182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 9a9dcb7a-7994-4f6a-85c5-7ebfefe6c14a · inbound

When Does Removing LayerNorm Help? Activation Bounding as a Regime-Dependent Implicit Regularizer cites this paper.

When Does Removing LayerNorm Help? Activation Bounding as a Regime-Dependent Implicit Regularizer Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-11T20:36:10.321368Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation c0dc39b1-a0ee-4ea3-b7d2-21ab322a31f0 · inbound

Dead Directions: Geometric Singular Learning cites this paper.

Dead Directions: Geometric Singular Learning Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 21

Resolution: verified exact; arxiv_id, observed 2026-07-02T11:36:55.173661Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation e0605a6f-b5f6-43ad-b366-a132f84ce771 · inbound

Algebraic Dead Directions in LayerNorm Transformers: A Forward-Pass-Only Diagnostic at LLM Scale cites this paper.

Algebraic Dead Directions in LayerNorm Transformers: A Forward-Pass-Only Diagnostic at LLM Scale Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:29:15.314353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 04607fde-e876-48eb-a945-022b466d8c50 · inbound

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors cites this paper.

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 98

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T20:30:07.742267Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

Observation 688d377c-aa05-4460-9e65-c8e76ea8e7f5 · inbound

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors cites this paper.

Improving Neural Network Training by Decoupling the Magnitude and Direction of Weight Vectors Peri-LN: Revisiting Normalization Layer in the Transformer Architecture

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-02T10:14:07.666821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.