Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2305.18270.
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 2026-08-07T14:40:54.621375Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T07:06:44.997380Z
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 538f54cd-b6d1-4db0-a809-544ffa8652d4 · 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 How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:40:54.621375Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b92bcd50-dfe8-41fa-8cef-b6b523db09c1 · inbound
How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability cites this paper.
How Do Transformers Learn to Associate Tokens: Gradient Leading Terms Bring Mechanistic Interpretability How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T11:20:52.659015Z
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 eec2132c-6579-4d21-98d0-7bf1a82f197e · inbound
Why Muon Outperforms Adam: A Curvature Perspective cites this paper.
Why Muon Outperforms Adam: A Curvature Perspective How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Reference 46
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T07:06:44.999214Z
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 faf00f46-23d0-4e6b-a86c-1129ebdfc471 · inbound
Spectral phase transitions and trainability in neural network learning dynamics cites this paper.
Spectral phase transitions and trainability in neural network learning dynamics How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T15:35:47.552849Z
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 35c1a2cd-d361-4f9c-bc7f-b499cafbcb1c · inbound
The Multiscale Single-Index Model: A Stylized Model for Hierarchical Feature Learning cites this paper.
The Multiscale Single-Index Model: A Stylized Model for Hierarchical Feature Learning How Two-Layer Neural Networks Learn, One (Giant) Step at a Time
Reference 25
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T03:07:54.001891Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.