Paper Citation Record · LEDGER

RePaint: Inpainting using Denoising Diffusion Probabilistic Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2201.09865.

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

pith.paper-citation-record.v1
2201.09865 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T11:22:49.512965Z

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

74
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 9c592cc7-0cfc-45a1-8e90-24bc5bf87543 · inbound

DreamFusion: Text-to-3D using 2D Diffusion cites this paper.

DreamFusion: Text-to-3D using 2D Diffusion RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 43

Resolution: verified exact; arxiv_id, observed 2026-05-11T11:27:10.471269Z

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 45b0b734-c637-44bf-b767-bed8c1c018d1 · inbound

Rethinking Machine Unlearning in Image Generation Models cites this paper.

Rethinking Machine Unlearning in Image Generation Models RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T11:22:49.512965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 74a9080a-25d8-478b-87c3-5896a4934560 · inbound

Fusion of multi-source precipitation records via coordinate-based generative model cites this paper.

Fusion of multi-source precipitation records via coordinate-based generative model RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-07T04:07:50.808163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0eed5145-9d70-4f1f-8a34-13600544c75d · inbound

WaveLLDM: Design and Development of a Lightweight Latent Diffusion Model for Speech Enhancement and Restoration cites this paper.

WaveLLDM: Design and Development of a Lightweight Latent Diffusion Model for Speech Enhancement and Restoration RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-05T14:36:37.628215Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c30f58f-1cbb-4854-a268-ecdc8a1f6ceb · inbound

ART-VITON: Measurement-Guided Latent Diffusion for Artifact-Free Virtual Try-On cites this paper.

ART-VITON: Measurement-Guided Latent Diffusion for Artifact-Free Virtual Try-On RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-18T13:26:24.772424Z

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 4ae115bc-f664-4114-ab1f-306ee45336fc · inbound

Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions cites this paper.

Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-03T12:45:03.615247Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8bc4e53-ebce-4226-8d8e-204833ebecb4 · inbound

A Guided Unconditional Diffusion Model to Synthesize and Inpaint Radio Galaxies from FIRST, MGCLS and Radio Zoo cites this paper.

A Guided Unconditional Diffusion Model to Synthesize and Inpaint Radio Galaxies from FIRST, MGCLS and Radio Zoo RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-03T11:08:07.699070Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6223b663-04a4-4c5c-8fac-531ddbdaacdb · inbound

PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios cites this paper.

PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-10T14:20:30.597514Z

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 6b826147-c4c0-4fe0-a931-d2805cdbb215 · inbound

$Z^2$-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models cites this paper.

$Z^2$-Sampling: Zero-Cost Zigzag Trajectories for Semantic Alignment in Diffusion Models RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 27

Resolution: verified exact; arxiv_id, observed 2026-05-11T21:06:15.024809Z

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 8d3db193-7270-4d52-a750-9515c30591e6 · inbound

Generative diffusion models for spatiotemporal influenza forecasting cites this paper.

Generative diffusion models for spatiotemporal influenza forecasting RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 14

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T00:09:29.516611Z

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 6f918a48-0635-4a35-9294-d46bdbbbb181 · inbound

AsyncPatch Diffusion: spatially-flexible image generation cites this paper.

AsyncPatch Diffusion: spatially-flexible image generation RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 29

Resolution: verified exact; arxiv_id, observed 2026-07-02T16:37:09.227990Z

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 59cbcaa2-ec70-46d8-b82e-354005eb4bd0 · inbound

Do as I Do: Dexterous Manipulation Data from Everyday Human Videos cites this paper.

Do as I Do: Dexterous Manipulation Data from Everyday Human Videos RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 66

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:59:19.359292Z

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 8d64d044-8a16-4445-a8e4-2c7cc8cec7cc · inbound

MakeupMirror: Improving Facial Attribute Preservation in Diffusion Models for Makeup Transfer cites this paper.

MakeupMirror: Improving Facial Attribute Preservation in Diffusion Models for Makeup Transfer RePaint: Inpainting using Denoising Diffusion Probabilistic Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-04T03:29:30.655810Z

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.