Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2603.18907.
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 2026-08-02T12:03:42.240334Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-03T00:47:29.728746Z
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 4ac8749e-db75-4f44-8511-7de56f9e19a0 · inbound
Neural Galerkin Normalizing Flows for Bayesian Inference of Diffusions with Inaccessible Boundaries cites this paper.
Neural Galerkin Normalizing Flows for Bayesian Inference of Diffusions with Inaccessible Boundaries Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models
Reference 21
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T06:06:41.613719Z
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 a7e19f21-baec-42a7-b833-b82956ae5faa · inbound
A transition-density-based operator learning method for Fokker-Planck equations with various initial conditions cites this paper.
A transition-density-based operator learning method for Fokker-Planck equations with various initial conditions Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models
Reference 55
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-03T00:47:29.730365Z
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 d51e5b01-b4ca-4aed-8333-57f6fa07770d · inbound
A transition-density-based operator learning method for Fokker-Planck equations with various initial conditions cites this paper.
A transition-density-based operator learning method for Fokker-Planck equations with various initial conditions Neural Galerkin Normalizing Flow for Transition Probability Density Functions of Diffusion Models
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T12:03:42.240334Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.