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Paper Citation Record · LEDGER

CutPaste: Self-Supervised Learning for Anomaly Detection and Localization

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2104.04015.

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

pith.paper-citation-record.v1
2104.04015 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 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T12:25:55.169336Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-03T00:17:28.729692Z

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 d0d8fb91-0e1b-48b3-8987-e376527ed0a8 · inbound

3D-PNAS: 3D Industrial Surface Anomaly Synthesis with Perlin Noise cites this paper.

3D-PNAS: 3D Industrial Surface Anomaly Synthesis with Perlin Noise CutPaste: Self-Supervised Learning for Anomaly Detection and Localization

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-16T12:25:55.169336Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-16T12:25:55.169336Z digest=sha256:d6b5df7494254360cb108260d838d23666516df88d54fff692f4766a628084c2

Observation 7f48db67-948e-41aa-90d3-4a873ba31c9b · inbound

Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision cites this paper.

Visual Prompting Meets Feature Reconstruction-Based Anomaly Detection with Dual-Teacher Supervision CutPaste: Self-Supervised Learning for Anomaly Detection and Localization

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:17:28.731293Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-06-27T17:23:13.494169Z digest=sha256:9c1532fde2ca3b90576b0f0de160d92a6e6e062ecc8f30a1e22cc9144564e5ef