Paper Citation Record · LEDGER

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues

As of 7 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 1 inbound Pith citation observation for arXiv:2602.23039.

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

pith.paper-citation-record.v1
2602.23039 v2

Coverage vector

measured 36 of 36 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T20:37:01.605875Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-25T03:16:34.488732Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T03:20:17.010340Z

Reference resolution

36 of 36 outbound references displayed

verified exact6
verified fuzzy0
unresolved30
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f859896f-8249-4e32-9a29-1f995e77bf2d · outbound

This paper cites write newline.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:58.610776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 186d3b0c-13dc-456a-9766-c2099a579921 · outbound

This paper cites S., Saxe, A.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues S., Saxe, A

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:58.697950Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6ea5d55-b74a-4a43-ab8c-3030b546597a · outbound

This paper cites A dynamical model of neural scaling laws.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues A dynamical model of neural scaling laws

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:58.789632Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51ebd841-dadb-46f6-ac05-27fb6855392d · outbound

This paper cites How feature learning can improve neural scaling laws.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues How feature learning can improve neural scaling laws

Reference 4

Resolution: verified exact; doi, observed 2026-08-02T20:39:34.544742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 01d4e56e-64ba-49bc-9d1a-f76438fbcc3c · outbound

This paper cites and Paruch, P.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues and Paruch, P

Reference 5

Resolution: verified exact; doi, observed 2026-08-02T20:39:34.383239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation 7dade971-b3ee-4dbe-a7ff-df8683f51ad3 · outbound

This paper cites Spectral bias and task-model alignment explain generalization in kernel regression and infinitely wide neural networks.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Spectral bias and task-model alignment explain generalization in kernel regression and infinitely wide neural networks

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:59.135952Z

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Observation 8871f1fc-6398-4d42-8f8b-519a1315e7cc · outbound

This paper cites P., Helias, M., and Ringel, Z.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues P., Helias, M., and Ringel, Z

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:59.213580Z

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Unavailable: canonical work link unavailable.

Observation eda96f91-fa7a-4d10-a1c9-b1728f6447da · outbound

This paper cites Techniques de renormalisation de la thÉorie des champs et dynamique des phÉnomÈnes critiques.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Techniques de renormalisation de la thÉorie des champs et dynamique des phÉnomÈnes critiques

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:59.323696Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 72ac46e7-6441-4c29-89c0-babd5346384b · outbound

This paper cites Dynamics as a substitute for replicas in systems with quenched random impurities.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Dynamics as a substitute for replicas in systems with quenched random impurities

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-02T20:36:59.553770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 87196cc2-5683-467e-84ac-e929462d37dc · outbound

This paper cites an unresolved cited work.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Unresolved cited work

Reference 10

Resolution: verified exact; doi, observed 2026-08-02T20:39:34.124742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation c4adf88e-03d6-4f83-abf9-e8760971b541 · outbound

This paper cites an unresolved cited work.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Unresolved cited work

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:00.043919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd2304f7-3674-4f81-8708-1016da986045 · outbound

This paper cites and Dahmen, D.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues and Dahmen, D

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:00.132378Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a4c3d8aa-3df6-42b0-93b7-030f89d033ef · outbound

This paper cites Neural tangent kernel: Convergence and generalization in neural networks.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Neural tangent kernel: Convergence and generalization in neural networks

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:00.221881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78ed4308-ef10-4e53-a908-8a759237ad06 · outbound

This paper cites Neural Tangent Kernel: Convergence and Generalization in Neural Networks.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Neural Tangent Kernel: Convergence and Generalization in Neural Networks

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:00.343884Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ff767916-00af-4021-ad91-7e24c928ebca · outbound

This paper cites On a lagrangean for classical field dynamics and renormalization group calculations of dynamical critical properties.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues On a lagrangean for classical field dynamics and renormalization group calculations of dynamical critical properties

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:00.465514Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1c634032-4b78-4956-b125-2389d7eaa45c · outbound

This paper cites Scaling Laws for Neural Language Models.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Scaling Laws for Neural Language Models

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:00.597494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 099b1bfb-f75f-4756-b23a-ed854d31fbf0 · outbound

This paper cites 1/f2 Characteristics and Isotropy in the Fourier Power Spectra of Visual Art , Cartoons , Comics , Mangas , and Different Categories of Photographs.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues 1/f2 Characteristics and Isotropy in the Fourier Power Spectra of Visual Art , Cartoons , Comics , Mangas , and Different Categories of Photographs

Reference 17

Resolution: verified exact; doi, observed 2026-08-02T20:39:33.654741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation d1de8b94-9cbd-419f-a09c-07e4d9e40cfe · outbound

This paper cites Learning with noise in a linear perceptron.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Learning with noise in a linear perceptron

Reference 18

Resolution: verified exact; doi, observed 2026-08-02T20:39:33.404746Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a3cf5268-e7aa-42b3-98d7-94a29505ceab · outbound

This paper cites and Hertz, J.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues and Hertz, J

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.043314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 65e9a31d-88bf-447a-81a1-5ca8a3881ecb · outbound

This paper cites and Hertz, J.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues and Hertz, J

Reference 20

Resolution: verified exact; doi, observed 2026-08-02T20:39:33.089090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

Observation a73e6885-3911-4ce0-92bd-2548f58b676c · outbound

This paper cites Adaptive kernel predictors from feature-learning infinite limits of neural networks.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Adaptive kernel predictors from feature-learning infinite limits of neural networks

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.243971Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 01cbdf4c-d3a1-44c9-9b5a-0e9bfa181e38 · outbound

This paper cites Deep neural networks as gaussian processes.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Deep neural networks as gaussian processes

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.375357Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dabc0be-c39b-4405-b2ca-a3c4c6b70461 · outbound

This paper cites and Sompolinsky, H.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues and Sompolinsky, H

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.523571Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5599f16-4da7-48d5-be98-7e5da2768231 · outbound

This paper cites A Solvable Model of Neural Scaling Laws.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues A Solvable Model of Neural Scaling Laws

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.571822Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ac31087-b81a-4110-b483-95bea73b7a62 · outbound

This paper cites Statistical dynamics of classical systems.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Statistical dynamics of classical systems

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.575075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 951fed26-1281-4785-8758-fdf77569aa5c · outbound

This paper cites Deep double descent: where bigger models and more data hurt*.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Deep double descent: where bigger models and more data hurt*

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.577934Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7d154cf5-2e15-4a99-abef-d16dfad8b8b4 · outbound

This paper cites Predicting the outputs of finite networks trained with journal = arXiv ,noisy gradients.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Predicting the outputs of finite networks trained with journal = arXiv ,noisy gradients

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.580643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78ef5e8b-fc20-42f0-b032-59d09bd146de · outbound

This paper cites an unresolved cited work.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Unresolved cited work

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.583459Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18fa7d63-4411-4e9e-b252-9d4f5b150625 · outbound

This paper cites A statistical mechanics framework for bayesian deep neural networks beyond the infinite-width limit.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues A statistical mechanics framework for bayesian deep neural networks beyond the infinite-width limit

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.586165Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 743e1edd-cda1-4578-9487-5ef075bf1b55 · outbound

This paper cites and Recht, B.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues and Recht, B

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.588887Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c4c94aa7-1cb5-4295-8165-3e9555019c3b · outbound

This paper cites From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues From Kernels to Features: A Multi-Scale Adaptive Theory of Feature Learning

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.591623Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 30397749-3540-4f1a-bacd-2dbb234432fb · outbound

This paper cites an unresolved cited work.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Unresolved cited work

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.594466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 482ed00f-7372-4a63-a603-bab8b694ada2 · outbound

This paper cites Separation of scales and a thermodynamic description of feature learning in some cnns.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Separation of scales and a thermodynamic description of feature learning in some cnns

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.597312Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a5067c29-2ac1-4dd6-aa6c-9268da03bc68 · outbound

This paper cites S., Sompolinsky, H., and Tishby, N.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues S., Sompolinsky, H., and Tishby, N

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.599859Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ad64b51-7f88-4f71-92c6-0c2493427b0c · outbound

This paper cites Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Learning in large linear perceptrons and why the thermodynamic limit is relevant to the real world

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.602393Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f5d2789a-8b82-4313-9eb3-8e8f2fa91fcb · outbound

This paper cites Computing with infinite networks.

Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues Computing with infinite networks

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-02T20:37:01.605875Z

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Unavailable: canonical work link unavailable.

Pith citing papers

Observation 02cfacee-3bb7-420c-9c9b-48624cf16e36 · inbound

Asymmetric Scaling Laws from Sparse Features cites this paper.

Asymmetric Scaling Laws from Sparse Features Dynamics of neural scaling laws in random feature regression with powerlaw-distributed kernel eigenvalues

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-02T03:04:39.307243Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.