Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models
As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.05928.
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 2026-08-23T06:30:58.430688+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-15T15:47:42.895701Z
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
1
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 52b9a5e0-cebf-4bee-9fac-9b992743c658 · inbound
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights cites this paper.
Transformers for Learning on Noisy and Task-Level Manifolds: Approximation and Generalization Insights The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models
Reference 10
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T16:01:46.035204Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.
Observation 058c8497-7809-493d-bb71-07f22dfaa99b · inbound
Geometric Metrics and LLMs: What They Measure and When They Work cites this paper.
Geometric Metrics and LLMs: What They Measure and When They Work The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T15:47:42.895701Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9aab1fcd-5778-4470-8640-48a8e840b2b2 · inbound
Contribution Weights: A Geometrical Analysis of Self-Attention Transformers cites this paper.
Contribution Weights: A Geometrical Analysis of Self-Attention Transformers The Shape of Learning: Anisotropy and Intrinsic Dimensions in Transformer-Based Models
Reference 73
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:32:46.710465Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.