Paper Citation Record · LEDGER

A Neural Scaling Law from the Dimension of the Data Manifold

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 15 inbound Pith citation observations for arXiv:2004.10802.

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

pith.paper-citation-record.v1
2004.10802 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 15 of 15 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T17:20:51.125775Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

20
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation a9141ef0-e807-4685-b4e5-41a9aa858e00 · inbound

Scaling Laws for Autoregressive Generative Modeling cites this paper.

Scaling Laws for Autoregressive Generative Modeling A Neural Scaling Law from the Dimension of the Data Manifold

Reference 22

Resolution: verified exact; arxiv_id, observed 2026-05-13T07:49:43.895674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 6d79df94-4f33-4540-8fa6-cd82031cf0ec · inbound

Scaling Laws for Transfer cites this paper.

Scaling Laws for Transfer A Neural Scaling Law from the Dimension of the Data Manifold

Reference 191

Resolution: verified exact; arxiv_id, observed 2026-05-18T00:58:13.656031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0710e9c7-9b51-41ce-96a1-3f21c68c9512 · inbound

A General Language Assistant as a Laboratory for Alignment cites this paper.

A General Language Assistant as a Laboratory for Alignment A Neural Scaling Law from the Dimension of the Data Manifold

Reference 70

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:22:59.509563Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 42ca8c58-16aa-4cde-9a02-ed6b84130ea6 · inbound

Language Models (Mostly) Know What They Know cites this paper.

Language Models (Mostly) Know What They Know A Neural Scaling Law from the Dimension of the Data Manifold

Reference 128

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T15:42:47.761613Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 0aebf783-0cc6-4aa9-8aae-bbbb1468547d · inbound

Scaling Laws for Reward Model Overoptimization cites this paper.

Scaling Laws for Reward Model Overoptimization A Neural Scaling Law from the Dimension of the Data Manifold

Reference 26

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:04:53.372341Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dfe019b1-d085-417d-8599-b2e80d345b53 · inbound

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling cites this paper.

Pythia: A Suite for Analyzing Large Language Models Across Training and Scaling A Neural Scaling Law from the Dimension of the Data Manifold

Reference 123

Resolution: verified exact; arxiv_id, observed 2026-05-15T17:45:17.787834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 3bd673b6-52b7-4c84-b86c-606cb0f4d83f · inbound

KAN: Kolmogorov-Arnold Networks cites this paper.

KAN: Kolmogorov-Arnold Networks A Neural Scaling Law from the Dimension of the Data Manifold

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T23:42:05.642351Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 1e084193-0deb-4a47-b554-cb77d6811c04 · inbound

Lessons from the Trenches on Reproducible Evaluation of Language Models cites this paper.

Lessons from the Trenches on Reproducible Evaluation of Language Models A Neural Scaling Law from the Dimension of the Data Manifold

Reference 30

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T18:44:49.722815Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation f16b1678-4431-4148-b383-ec80fc2d9635 · inbound

Physics of Skill Learning cites this paper.

Physics of Skill Learning A Neural Scaling Law from the Dimension of the Data Manifold

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-10T17:20:51.125775Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1b262d94-819f-4ca6-9f50-be955d3289ae · inbound

Foundation Models for Discovery and Exploration in Chemical Space cites this paper.

Foundation Models for Discovery and Exploration in Chemical Space A Neural Scaling Law from the Dimension of the Data Manifold

Reference 54

Resolution: verified exact; arxiv_id, observed 2026-05-18T05:52:25.024774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 054147c7-b1b0-4f21-bbef-0cc9fa6c6355 · inbound

From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression cites this paper.

From One-Pass SGD to Data Reuse: Mini-Batch Scaling Laws in Sketched Linear Regression A Neural Scaling Law from the Dimension of the Data Manifold

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-06-30T14:14:45.604784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 41ef147f-9a9c-447a-9647-d371573fe04b · inbound

Structure and Scale in Simplicial Sequence Modelling cites this paper.

Structure and Scale in Simplicial Sequence Modelling A Neural Scaling Law from the Dimension of the Data Manifold

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-07-01T21:16:14.965575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fa74ad3d-b3df-4380-bfc2-076965ddb0ca · inbound

Towards Engineering Scaling Laws with Pretraining Data Composition cites this paper.

Towards Engineering Scaling Laws with Pretraining Data Composition A Neural Scaling Law from the Dimension of the Data Manifold

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-07-04T05:49:36.774610Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation a1c48e8f-fe23-465a-9bc0-2d0d6053e4fa · inbound

Towards Engineering Scaling Laws with Pretraining Data Composition cites this paper.

Towards Engineering Scaling Laws with Pretraining Data Composition A Neural Scaling Law from the Dimension of the Data Manifold

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-06-30T11:34:38.085890Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation 90567edc-1359-4902-9cc2-b5d66ce9dec5 · inbound

Sketched Linear Contrastive Learning: Approximation, Optimization, and Statistical Scaling cites this paper.

Sketched Linear Contrastive Learning: Approximation, Optimization, and Statistical Scaling A Neural Scaling Law from the Dimension of the Data Manifold

Reference 8

Resolution: metadata mismatch; arxiv_id, observed 2026-07-04T12:59:52.802769Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.