Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2310.07891.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T23:28:49.707781Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-22T10:26:24.056269Z
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 d750e739-650d-4369-a2f2-b9c852d3ae32 · 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 A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T12:32:48.019302Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 75330558-2d30-44df-a8b6-0b709fc034cb · 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 A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T04:36:32.163578Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 42742066-ca17-402a-869b-5e1621cd70a6 · inbound
Precise gradient descent training dynamics for finite-width multi-layer neural networks cites this paper.
Precise gradient descent training dynamics for finite-width multi-layer neural networks A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T23:28:49.707781Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8c6bc133-db7d-4d50-96ba-3b2a052e71f5 · inbound
Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime cites this paper.
Scaling Laws and Spectra of Shallow Neural Networks in the Feature Learning Regime A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T13:54:28.744741Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd590f46-5a7c-4b5c-8684-74243d00723d · inbound
There Will Be a Scientific Theory of Deep Learning cites this paper.
There Will Be a Scientific Theory of Deep Learning A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Reference 14
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T15:21:09.035686Z
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.
Observation 51557685-2d88-4b76-9857-505dbea086d4 · 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 A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Reference 58
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T03:05:53.390460Z
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.
Observation ad71e8f5-6a6f-4d2a-aa81-3cd75f13ba0a · 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 A Theory of Non-Linear Feature Learning with One Gradient Step in Two-Layer Neural Networks
Reference 63
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T10:26:24.060591Z
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.