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Paper Citation Record · LEDGER

Visual Prompting via Image Inpainting

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2209.00647.

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

pith.paper-citation-record.v1
2209.00647 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 2026-08-07T05:41:30.946687Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T14:31:40.536471Z

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 96e6c109-c011-4b21-9f17-9ddb4e8b831f · inbound

gen2seg: Generative Models Enable Generalizable Instance Segmentation cites this paper.

gen2seg: Generative Models Enable Generalizable Instance Segmentation Visual Prompting via Image Inpainting

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:31:40.538573Z

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=2026-05-22T14:31:30.651144Z digest=sha256:19097155ca09fc0c25fe33252da14597d86cf0992e829d8759c6b2193c2cb352

Observation f2952e48-e6eb-479a-92d9-58e4bf31d0f7 · inbound

From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models cites this paper.

From Generation to Generalization: Emergent Few-Shot Learning in Video Diffusion Models Visual Prompting via Image Inpainting

Reference 3

Resolution
unresolved
no resolver link, observed 2026-08-07T05:41:30.946687Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T05:41:30.946687Z digest=sha256:d71c11debb97f4209a10e76ffd17902112e296eded8060c21da411916ea7861a