Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2407.09468.
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 2026-08-07T14:38:38.430953Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T06:16:43.604125Z
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 645c72e2-0a13-4fd7-b6c3-d423d5e8dfa5 · inbound
Self-Organizing Visual Prototypes for Non-Parametric Representation Learning cites this paper.
Self-Organizing Visual Prototypes for Non-Parametric Representation Learning Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:38:38.430953Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 11d3aa48-5eac-424c-bc2c-80e348c20d02 · inbound
Hyperbolic Deep Learning for Foundation Models: A Survey cites this paper.
Hyperbolic Deep Learning for Foundation Models: A Survey Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures
Reference 106
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T14:54:36.831628Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ba17be3f-a6ad-464b-8aad-d4bad8139cda · inbound
From Gradient Descent to Harmonic Interpolation: A Geometric Theory of Binary Classification cites this paper.
From Gradient Descent to Harmonic Interpolation: A Geometric Theory of Binary Classification Beyond Euclid: An Illustrated Guide to Modern Machine Learning with Geometric, Topological, and Algebraic Structures
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T06:16:43.605903Z
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.