Paper Citation Record · LEDGER

A Dynamical Model of Neural Scaling Laws

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 17 inbound Pith citation observations for arXiv:2402.01092.

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

pith.paper-citation-record.v1
2402.01092 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 17 of 17 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 17 of 17 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:54:36.817140Z

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

4
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 f1aa050a-3461-4a3a-a485-ffb0c08bc2e9 · inbound

Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer cites this paper.

Deep Linear Network Training Dynamics from Random Initialization: Data, Width, Depth, and Hyperparameter Transfer A Dynamical Model of Neural Scaling Laws

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-09T11:54:36.817140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9a8e5cdd-6d41-4973-a188-fbe1920d1554 · inbound

X-Factor: Quality Is a Dataset-Intrinsic Property cites this paper.

X-Factor: Quality Is a Dataset-Intrinsic Property A Dynamical Model of Neural Scaling Laws

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-07T13:06:54.228526Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 31e80633-1d77-41ee-a1d2-93a7ed7d0954 · inbound

Models of Heavy-Tailed Mechanistic Universality cites this paper.

Models of Heavy-Tailed Mechanistic Universality A Dynamical Model of Neural Scaling Laws

Reference 2004

Resolution: unresolved; no resolver link, observed 2026-08-07T11:15:49.556349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34cf55a9-2ec1-4ee3-979d-31fb7e50ae16 · 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 A Dynamical Model of Neural Scaling Laws

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-06T20:48:49.730886Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54141e33-4d4f-4ea4-b7f6-529e190d95f9 · inbound

Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime cites this paper.

Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime A Dynamical Model of Neural Scaling Laws

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T13:54:19.204690Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c3fe0d7-41f5-4e41-a177-840414a23fd1 · inbound

Unifying Learning Dynamics and Generalization in Transformers Scaling Law cites this paper.

Unifying Learning Dynamics and Generalization in Transformers Scaling Law A Dynamical Model of Neural Scaling Laws

Reference 2024

Resolution: unresolved; no resolver link, observed 2026-08-03T14:02:56.636048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9aa17211-cde2-4e59-b67f-b7786d3b6200 · inbound

Universal One-third Time Scaling in Learning Peaked Distributions cites this paper.

Universal One-third Time Scaling in Learning Peaked Distributions A Dynamical Model of Neural Scaling Laws

Reference 2020

Resolution: unresolved; no resolver link, observed 2026-08-03T05:01:10.886929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 85378cda-0043-4862-8178-49dd11c319e3 · inbound

Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory cites this paper.

Sharp Capacity Scaling of Spectral Optimizers in Learning Associative Memory A Dynamical Model of Neural Scaling Laws

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-05-14T23:38:16.414959Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a8fe1975-4b5c-4e89-8a55-b6230fc88da7 · inbound

There Will Be a Scientific Theory of Deep Learning cites this paper.

There Will Be a Scientific Theory of Deep Learning A Dynamical Model of Neural Scaling Laws

Reference 196

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:21:08.930094Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b034647a-485d-483e-b6ac-dfd8636e829a · inbound

Spectral Dynamics in Deep Networks: Feature Learning, Outlier Escape, and Learning Rate Transfer cites this paper.

Spectral Dynamics in Deep Networks: Feature Learning, Outlier Escape, and Learning Rate Transfer A Dynamical Model of Neural Scaling Laws

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:05:53.417008Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 01b099d1-ffe6-4036-a63e-8fa79a3dc133 · inbound

Spectral Dynamics in Deep Networks: Feature Learning, Outlier Escape, and Learning Rate Transfer cites this paper.

Spectral Dynamics in Deep Networks: Feature Learning, Outlier Escape, and Learning Rate Transfer A Dynamical Model of Neural Scaling Laws

Reference 46

Resolution: verified exact; arxiv_id, observed 2026-05-22T10:26:24.144053Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 5b4dae71-466b-47d6-b356-ce15c2a9b814 · inbound

Law of Neural Interaction: Depth-Width Shape, Interaction Efficiency, and Generalization cites this paper.

Law of Neural Interaction: Depth-Width Shape, Interaction Efficiency, and Generalization A Dynamical Model of Neural Scaling Laws

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:23:30.995018Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 34b0a212-0640-40ae-b2d0-522635e79063 · inbound

Theory of learning of high-dimensional controlled non-linear dynamical systems (I): models and methods cites this paper.

Theory of learning of high-dimensional controlled non-linear dynamical systems (I): models and methods A Dynamical Model of Neural Scaling Laws

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-02T20:27:22.486225Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b0b2aac8-44b9-4576-8e61-33c725439142 · inbound

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal cites this paper.

Anatomy of Post-Training: Using Interpretability to Characterize Data and Shape the Learning Signal A Dynamical Model of Neural Scaling Laws

Reference 221

Resolution: metadata mismatch; arxiv_id, observed 2026-07-03T09:07:47.897562Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation d371a118-ee7f-44e0-b894-60b77b20fcb5 · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization A Dynamical Model of Neural Scaling Laws

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-26T15:39:33.215383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b31f68df-0792-459b-ae8f-a6a06398f6f5 · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization A Dynamical Model of Neural Scaling Laws

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-07-02T21:57:25.330978Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation bfc5119a-3f4d-4e55-ada4-cc6b645d08fa · inbound

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients cites this paper.

Neural Scaling Universality: If Exponents Are Fixed, Time to Understand Coefficients A Dynamical Model of Neural Scaling Laws

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-07-04T17:20:00.850532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.