Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Persistent Topological Features in Large Language Models
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2410.11042.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-05T00:16:15.515774Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-04T02:59:25.646822Z
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 90a1df3d-cd41-4395-a461-4d5e7ea87589 · inbound
From Persistence to Survival: Hypothesis Testing, Effect Sizes and Vectorisation for Topological Features cites this paper.
From Persistence to Survival: Hypothesis Testing, Effect Sizes and Vectorisation for Topological Features Persistent Topological Features in Large Language Models
Reference 72
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T13:18:12.742625Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation f3c86944-198a-49d2-9030-43eca28140f8 · inbound
Patnaik-Pearson intrinsic dimension for internal representations of neural networks cites this paper.
Patnaik-Pearson intrinsic dimension for internal representations of neural networks Persistent Topological Features in Large Language Models
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-04T02:59:25.649125Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation deb8e21a-0127-478b-858a-3f9277b88ba0 · inbound
Patnaik-Pearson intrinsic dimension for internal representations of neural networks cites this paper.
Patnaik-Pearson intrinsic dimension for internal representations of neural networks Persistent Topological Features in Large Language Models
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T23:49:02.153185Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation a047529b-d383-4ef3-808e-d60e3b4f48ab · inbound
Tracking Representation Dynamics in Large Language Models with Persistent Homology cites this paper.
Tracking Representation Dynamics in Large Language Models with Persistent Homology Persistent Topological Features in Large Language Models
Reference 5
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-04T00:39:17.241167Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation feb4b702-64fe-444e-9d6c-98f9063b9219 · inbound
Isotropy Cliffs: The Geometric Signature of Decision-Making in Large Language Models cites this paper.
Isotropy Cliffs: The Geometric Signature of Decision-Making in Large Language Models Persistent Topological Features in Large Language Models
Reference 34
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T00:16:15.515774Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.