Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
On Feature Learning in Neural Networks with Global Convergence Guarantees
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2204.10782.
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 2026-08-17T06:30:58.91139+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T20:58:55.123804Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T10:29:44.296271Z
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 571ac4d5-d302-459c-baa9-2356614b3feb · inbound
Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs cites this paper.
Gradient flow dynamics of shallow ReLU networks for square loss and orthogonal inputs On Feature Learning in Neural Networks with Global Convergence Guarantees
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-24T11:29:24.892073Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.
Observation 06c6b081-df56-4ae3-87e3-37786a5ea7b0 · inbound
A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models cites this paper.
A Local Polyak-Lojasiewicz and Descent Lemma of Gradient Descent For Overparametrized Linear Models On Feature Learning in Neural Networks with Global Convergence Guarantees
Reference 4
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T20:58:55.123804Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f9b58d2d-bbfc-4766-b42b-6d1cd714bf88 · inbound
Convergence of Gradient Descent for General Neural Network Architectures Beyond the NTK Regime cites this paper.
Convergence of Gradient Descent for General Neural Network Architectures Beyond the NTK Regime On Feature Learning in Neural Networks with Global Convergence Guarantees
Reference 73
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T10:29:44.298043Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.