Pith. sign in

Paper Citation Record · LEDGER

Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2205.09653.

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

pith.paper-citation-record.v1
2205.09653 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T11:54:36.807310Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T15:33:32.761604Z

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 c09b42b8-6058-441a-a813-1c79c1436f24 · 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 Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-09T11:54:36.807310Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T11:54:36.807310Z digest=sha256:0aa2670b8d775c25872ebadb6239a602256906b8662e1ae20574225d03603fa8

Observation 202dfba4-7359-4e73-bd69-54180ad414ba · inbound

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

Adaptive kernel predictors from feature-learning infinite limits of neural networks Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-08T11:19:06.844013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T11:19:06.844013Z digest=sha256:dcd9c2f3759058abedcf0efb30008e62e69499583ed086b5b7ba3bbbb9999f59

Observation 0f53b237-1ee3-4f3f-8777-2d819628fd07 · 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 Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-11T03:05:53.506199Z

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.

source=pdf_text observed=2026-05-11T03:02:52.833353Z digest=sha256:092c30164c0fcaececc47d7673778c8cace5cfd8108c28da771b867fad1e85f3

Observation 6c517513-1376-4aed-bb5b-d83795fdeabe · 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 Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-22T10:26:24.174016Z

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.

source=pdf_text observed=2026-05-22T10:25:54.649302Z digest=sha256:e5e36fe6f0194fe11cd63dc36cfa8a0b0b9a595e4e0aee4b049b4da1f3f3522f

Observation 73ae7cc9-7b3b-4916-9878-1177c80e5e69 · inbound

Solitonic Construction of Artificial Neural Networks from Nonlinear Field Theory cites this paper.

Solitonic Construction of Artificial Neural Networks from Nonlinear Field Theory Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-29T15:33:32.763204Z

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.

source=pdf_text observed=2026-06-29T15:32:58.271444Z digest=sha256:166b04216c44e237c8f0be53e46ba77ff8ba5b19390e68393c1746721e09d774

Observation a6d4521b-14ec-4c0f-9046-325459e8c5e5 · inbound

Pre-Strings Lectures on Artificial Intelligence cites this paper.

Pre-Strings Lectures on Artificial Intelligence Self-Consistent Dynamical Field Theory of Kernel Evolution in Wide Neural Networks

Reference 53

Resolution
unresolved
no resolver link, observed 2026-07-12T06:14:03.658427Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T06:14:03.658427Z digest=sha256:9c2b918d8092f0fa5eba6f63f8b440631c998e101b75b724f2dc163524792710