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Paper Citation Record · LEDGER

Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2007.04596.

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

pith.paper-citation-record.v1
2007.04596 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:15:20.752317Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:27:30.131651Z

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 8133beb4-0d7d-4fe7-8b13-59e2e82bd60c · inbound

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings cites this paper.

How Learnable Grids Recover Fine Detail in Low Dimensions: A Neural Tangent Kernel Analysis of Multigrid Parametric Encodings Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-16T12:15:20.752317Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T12:15:20.752317Z digest=sha256:d23a7f4e94f72a2863591a8bdcaa5cdd917d7fd53c1eb88ede62d32961070528

Observation b5ec147e-af05-42d5-816c-2628dc1b0be0 · inbound

Feature learning is decoupled from generalization in high capacity neural networks cites this paper.

Feature learning is decoupled from generalization in high capacity neural networks Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T14:17:37.143199Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T14:17:37.143199Z digest=sha256:eecff5078fe7b6f059141f7dd6e71463fa36e7f8f281e9d47f429c10ce3aae05

Observation 17aa2916-7a2a-481e-bc47-1745551c572b · inbound

Muon Learns More Robust and Transferable Features than Adam cites this paper.

Muon Learns More Robust and Transferable Features than Adam Learning Over-Parametrized Two-Layer ReLU Neural Networks beyond NTK

Reference 128

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:27:30.134827Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-27T17:08:30.717799Z digest=sha256:79724576857af2993bbb6ae96104f777c0688f64c3df6743ef3ce255425f2c93