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Paper Citation Record · LEDGER

PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2011.08785.

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

pith.paper-citation-record.v1
2011.08785 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 2026-08-07T06:34:17.273281+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-05T17:39:19.453081Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T19:40:06.740949Z

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 463a3cdf-c0ee-48d8-a92b-8cd048b6a7d1 · inbound

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection cites this paper.

Wavelet-Enhanced PaDiM for Industrial Anomaly Detection PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-05T17:39:19.453081Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T17:39:19.453081Z digest=sha256:b25d6d56b1d3bc7268041ddfbf409bae71c18688ea2f442be467f23cd4a685e4

Observation d7731029-b18a-4c8c-a7e6-b82a88807c61 · inbound

HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection cites this paper.

HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-16T03:07:11.878218Z

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=2026-05-16T03:05:37.320403Z digest=sha256:4fdddccae9794e24aa5ef6a848848421a528c55bc6096a2494de916bb4a47a20

Observation e3b73cc1-9c6f-4e3a-aab8-0ec0144a99bd · inbound

Hypergraph Normal World Models for Logical Visual Anomaly Detection cites this paper.

Hypergraph Normal World Models for Logical Visual Anomaly Detection PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

Reference 7

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T19:40:06.742418Z

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=2026-06-25T21:09:19.682153Z digest=sha256:475453b277b10618027eeddaf5e2e5105cd9eaf95460a01bb0b45a544a282eb6

Observation 3bf5b7cc-8e37-484c-8170-d30407e93804 · inbound

Benchmark AUC Is Not Deployable Reliability: A Cross-Dataset Audit of Off-the-Shelf Features for Surveillance Video Anomaly Detection cites this paper.

Benchmark AUC Is Not Deployable Reliability: A Cross-Dataset Audit of Off-the-Shelf Features for Surveillance Video Anomaly Detection PaDiM: a Patch Distribution Modeling Framework for Anomaly Detection and Localization

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T07:34:21.582900Z

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=2026-06-30T07:29:32.843624Z digest=sha256:328dc963df8719c61ce8b38554f066d898d6cce974ee60a551680173d148ec63