Paper Citation Record · LEDGER

Asymptotics of feature learning in two-layer networks after one gradient-step

As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2402.04980.

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

pith.paper-citation-record.v1
2402.04980 v2

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 2026-08-16T06:30:59.297886+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T12:32:47.934162Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T10:26:24.078559Z

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 7493948f-df03-49f4-8a78-95a3fc1e4829 · inbound

Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks cites this paper.

Learning Hierarchical Polynomials of Multiple Nonlinear Features with Three-Layer Networks Asymptotics of feature learning in two-layer networks after one gradient-step

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-12T12:32:47.934162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3517b08a-6313-4d32-8b1c-26d7ae5548c7 · inbound

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories cites this paper.

Towards a Statistical Understanding of Neural Networks: Beyond the Neural Tangent Kernel Theories Asymptotics of feature learning in two-layer networks after one gradient-step

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-11T04:36:32.038109Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 352123a2-0135-441e-a60a-08d45de714b3 · inbound

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

There Will Be a Scientific Theory of Deep Learning Asymptotics of feature learning in two-layer networks after one gradient-step

Reference 23

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T15:21:09.081336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c096a96d-7078-4491-9a08-234b091df4fd · 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 Asymptotics of feature learning in two-layer networks after one gradient-step

Reference 60

Resolution: verified exact; arxiv_id, observed 2026-05-11T03:05:53.378689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 18d68e42-ddd8-4826-9f5f-a977181f00a0 · 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 Asymptotics of feature learning in two-layer networks after one gradient-step

Reference 65

Resolution: verified exact; arxiv_id, observed 2026-05-22T10:26:24.083646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 3827d155-278d-4b55-830c-408150666751 · inbound

The Multiscale Single-Index Model: A Stylized Model for Hierarchical Feature Learning cites this paper.

The Multiscale Single-Index Model: A Stylized Model for Hierarchical Feature Learning Asymptotics of feature learning in two-layer networks after one gradient-step

Reference 16

Resolution: unresolved; no resolver link, observed 2026-07-12T03:07:54.001891Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.