Paper Citation Record · LEDGER

How to set AdamW's weight decay as you scale model and dataset size

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2405.13698.

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

pith.paper-citation-record.v1
2405.13698 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T01:03:53.162526Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T20:30:07.608050Z

Reference resolution

0 of 0 outbound references displayed

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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 90af06df-b171-4857-bc55-902473b9d5df · inbound

$\mu$nit Scaling: Simple and Scalable FP8 LLM Training cites this paper.

$\mu$nit Scaling: Simple and Scalable FP8 LLM Training How to set AdamW's weight decay as you scale model and dataset size

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-08T17:19:29.237555Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 43490163-c4d2-4809-872b-533a1ae5444d · inbound

Practical Efficiency of Muon for Pretraining cites this paper.

Practical Efficiency of Muon for Pretraining How to set AdamW's weight decay as you scale model and dataset size

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T01:03:53.162526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2a802f31-d8a0-4a08-a5ba-7884a5a91ec3 · inbound

MuLoCo: Muon is a practical inner optimizer for DiLoCo cites this paper.

MuLoCo: Muon is a practical inner optimizer for DiLoCo How to set AdamW's weight decay as you scale model and dataset size

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-07T12:45:30.277440Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 16c13459-0ce0-4da9-8d2f-dab0399daa4c · inbound

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks cites this paper.

Scaling Collapse Reveals Universal Dynamics in Compute-Optimally Trained Neural Networks How to set AdamW's weight decay as you scale model and dataset size

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T20:48:54.538611Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b442b740-5ea5-493a-b93e-605a2a8ff4ac · inbound

Weight Decay Improves Language Model Plasticity cites this paper.

Weight Decay Improves Language Model Plasticity How to set AdamW's weight decay as you scale model and dataset size

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-03T00:15:37.343946Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 62b52619-7bc6-46fd-90cd-b5cbe7b9bb18 · inbound

Rethinking Language Model Scaling under Transferable Hypersphere Optimization cites this paper.

Rethinking Language Model Scaling under Transferable Hypersphere Optimization How to set AdamW's weight decay as you scale model and dataset size

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-14T21:53:02.441467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation b57ebadf-4f86-465b-9aff-eab0e2766a85 · inbound

GQA-{\mu}P: The maximal parameterization update for grouped query attention cites this paper.

GQA-{\mu}P: The maximal parameterization update for grouped query attention How to set AdamW's weight decay as you scale model and dataset size

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-19T16:37:39.822671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 347648e8-8a1f-4e37-9355-d8eec62b6283 · inbound

A Two-Parameter Weibull Framework for Diagnosing Transformer Weight Distributions cites this paper.

A Two-Parameter Weibull Framework for Diagnosing Transformer Weight Distributions How to set AdamW's weight decay as you scale model and dataset size

Reference 32

Resolution: verified exact; arxiv_id, observed 2026-05-20T14:23:21.546428Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation f297a98d-c26e-4bc0-a89f-45ca90684f91 · inbound

Muon Learns More Robust and Transferable Features than Adam cites this paper.

Muon Learns More Robust and Transferable Features than Adam How to set AdamW's weight decay as you scale model and dataset size

Reference 33

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T00:27:30.106422Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 0a73887b-e141-43ab-ad54-9fd14da19f9b · 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 How to set AdamW's weight decay as you scale model and dataset size

Reference 81

Resolution: verified exact; arxiv_id, observed 2026-07-04T20:30:07.609833Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

Observation 30de1928-ab05-4104-8e23-21758f905ff7 · 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 How to set AdamW's weight decay as you scale model and dataset size

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-02T10:14:12.180596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.