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Paper Citation Record · LEDGER

Metrics for Probabilistic Geometries

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:1411.7432.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
1411.7432 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:31:47.292160Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-06T15:39:01.194563Z

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 94c539cb-827e-4364-8bda-4cc515e6e51f · inbound

Hessian Geometry of Latent Space in Generative Models cites this paper.

Hessian Geometry of Latent Space in Generative Models Metrics for Probabilistic Geometries

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T04:31:47.292160Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T04:31:47.292160Z digest=sha256:a1024490824a2bddfb6e2c42fb02f0f4458b209c253747f0106da5c275e02c82

Observation 2f6e787a-5748-4a20-8375-a3da2b5ce209 · inbound

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds cites this paper.

Intrinsic-Hybrid Latent Diffusion Models for Generative Modeling on Unknown Manifolds Metrics for Probabilistic Geometries

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-06T15:39:01.235383Z

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.

source=pdf_text observed=2026-08-06T15:38:59.262760Z digest=sha256:0c91bd2d9893dbdc98ab66c20e172ee3cff5228918588af58a5c85b8b5fefea3