Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2411.08798.
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 2026-08-10T06:31:04.303077+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T11:55:22.722535Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-19T08:57:13.209454Z
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 bec2f032-1b56-49ec-afb6-cc60000548b6 · inbound
Optimal Spectral Transitions in High-Dimensional Multi-Index Models cites this paper.
Optimal Spectral Transitions in High-Dimensional Multi-Index Models Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
Reference 49
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T11:55:22.722535Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a434cd0-e0c5-43b0-874a-eb511ba7a4a8 · inbound
Flat Channels to Infinity in Neural Loss Landscapes cites this paper.
Flat Channels to Infinity in Neural Loss Landscapes Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-19T08:57:13.213345Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.
Observation 605adf10-3aa7-4f64-a1cd-cfa94ee8376a · inbound
Scaling Laws from Sequential Feature Recovery: A Solvable Hierarchical Model cites this paper.
Scaling Laws from Sequential Feature Recovery: A Solvable Hierarchical Model Learning Gaussian Multi-Index Models with Gradient Flow: Time Complexity and Directional Convergence
Reference 94
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-15T01:39:38.376465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.