Paper Citation Record · LEDGER

Diffusion-PINN Sampler

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2410.15336.

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

pith.paper-citation-record.v1
2410.15336 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T19:28:40.164420Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T20:17:33.792224Z

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 ece942cb-17c5-4bbc-a8ec-f4ce15a2a66e · inbound

Towards Adaptive External Communication in Autonomous Vehicles: A Conceptual Design Framework cites this paper.

Towards Adaptive External Communication in Autonomous Vehicles: A Conceptual Design Framework Diffusion-PINN Sampler

Reference 116

Resolution: unresolved; no resolver link, observed 2026-08-05T19:28:40.164420Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 630de95d-bfd2-451c-b0ab-21ffd0769897 · inbound

A Diffusive Classification Loss for Learning Energy-based Generative Models cites this paper.

A Diffusive Classification Loss for Learning Energy-based Generative Models Diffusion-PINN Sampler

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-22T12:11:31.225237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.

Observation af14beb0-8023-468f-abce-b33c0fe3b61b · inbound

Diffusion-based Annealed Boltzmann Generators : benefits, pitfalls and hopes cites this paper.

Diffusion-based Annealed Boltzmann Generators : benefits, pitfalls and hopes Diffusion-PINN Sampler

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-03T07:12:56.204163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a30caa8-20d0-4de1-82b2-763a12a16cf3 · inbound

Tensor Train Diffusion: Leveraging Low-Rank Structures for High-Dimensional Score-Based Sampling cites this paper.

Tensor Train Diffusion: Leveraging Low-Rank Structures for High-Dimensional Score-Based Sampling Diffusion-PINN Sampler

Reference 10

Resolution: metadata mismatch; local_arxiv, observed 2026-07-10T20:17:33.793452Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.