Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.15459.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:40:54.390971Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T12:04:38.769434Z
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 77158d68-8908-4806-9133-922debe71e6c · inbound
On the Mechanisms of Weak-to-Strong Generalization: A Theoretical Perspective cites this paper.
On the Mechanisms of Weak-to-Strong Generalization: A Theoretical Perspective Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Reference 2023
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:40:54.390971Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 90d0321a-5735-4f92-959a-e46a227a22f9 · inbound
Scaling Laws from Sequential Feature Recovery: A Solvable Hierarchical Model cites this paper.
Scaling Laws from Sequential Feature Recovery: A Solvable Hierarchical Model Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Reference 166
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-15T01:39:38.361285Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation fd157416-7612-468c-82eb-d28254755e62 · inbound
Average Gradient Outer Product in kernel regression provably recovers the central subspace for multi-index models cites this paper.
Average Gradient Outer Product in kernel regression provably recovers the central subspace for multi-index models Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T03:14:53.232224Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 3398e3d1-7dda-44d3-8b4e-544a0252fc96 · inbound
How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis cites this paper.
How Neural Reward Models Learn Features for Policy Optimization: A Single-Index Analysis Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T12:04:38.771038Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 0d43a4f8-e80f-443b-a125-1d097146c688 · inbound
Approximate Message Passing with Random Initialization for Phase Retrieval cites this paper.
Approximate Message Passing with Random Initialization for Phase Retrieval Repetita Iuvant: Data Repetition Allows SGD to Learn High-Dimensional Multi-Index Functions
Reference 19
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:35:23.380334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.