Paper Citation Record · LEDGER

PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2302.04265.

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

pith.paper-citation-record.v1
2302.04265 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:52:24.681026Z

measured 1 of 1 external citation measurements

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

11
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 26488ff3-b7d3-4423-ab2a-d2905dd0fbe4 · inbound

Optical Physics-Based Generative Models cites this paper.

Optical Physics-Based Generative Models PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T10:52:24.681026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8044aa8-94bd-48e9-b2e5-e408c21439c5 · inbound

Generative models on phase space cites this paper.

Generative models on phase space PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Reference 42

Resolution: verified exact; arxiv_id, observed 2026-05-13T20:53:15.441015Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 9564e121-d6cb-468e-b862-ed75c77a6c0b · inbound

Deepfake Detection Generalization with Diffusion Noise cites this paper.

Deepfake Detection Generalization with Diffusion Noise PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Reference 75

Resolution: verified exact; arxiv_id, observed 2026-05-10T11:25:19.434111Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1b016c92-8e4a-4e05-afac-400d147c1767 · inbound

The two clocks and the innovation window: When and how generative models learn rules cites this paper.

The two clocks and the innovation window: When and how generative models learn rules PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Reference 59

Resolution: verified exact; arxiv_id, observed 2026-05-12T03:16:18.061098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4cef09ea-6555-4a27-a592-cac9df0bb19a · inbound

Beckmann Transport Models: From Autonomous Flows to One-Step Maps cites this paper.

Beckmann Transport Models: From Autonomous Flows to One-Step Maps PFGM++: Unlocking the Potential of Physics-Inspired Generative Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T00:16:56.584959Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.