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Paper Citation Record · LEDGER

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

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 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 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-12T03:07:54.001891Z

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 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 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-05-09T20:11:17.616190Z digest=sha256:362dfb3c44121e747dc90834377541444f36ebfe69e3c7b07c1c88f6ddd77503

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-11T03:02:52.833353Z digest=sha256:2760d83f7c725966a90663fc3b8202cdb02289dfd593bae1212bf1d68c607337

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 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-22T10:25:54.649302Z digest=sha256:8cb75d9004d12e657d9734afc57977793b9ac2199198070bfb406b93c4ad0383

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.

source=arxiv_source observed=2026-07-12T03:07:54.001891Z digest=sha256:badd84015f756489df61f0facb76cc0512abf2ada7d2f943fa88704a9a1ef63f