Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
As of 5 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2205.01445.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-06-30T01:22:17.359656Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation abf84bb4-9c10-4673-b935-749f972b6cb5 · inbound
Sharp convergence rates for Spectral methods via the feature space decomposition method cites this paper.
Sharp convergence rates for Spectral methods via the feature space decomposition method High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Reference 3
- Resolution
- verified exact
- arxiv_id, observed 2026-05-21T17:34:17.291745Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation cb80a9ad-fa46-435a-b81f-c1b52a47a47c · inbound
The Benefits of Temporal Correlations: SGD Learns k-Juntas from Random Walks Efficiently cites this paper.
The Benefits of Temporal Correlations: SGD Learns k-Juntas from Random Walks Efficiently High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Reference 3
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-12T05:31:22.885759Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 72d5132f-f84e-42f0-aae8-2eacff7a69b1 · inbound
Spectral phase transitions and trainability in neural network learning dynamics cites this paper.
Spectral phase transitions and trainability in neural network learning dynamics High-dimensional Asymptotics of Feature Learning: How One Gradient Step Improves the Representation
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T15:35:47.479702Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.