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Paper Citation Record · LEDGER

DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2312.06607.

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

pith.paper-citation-record.v1
2312.06607 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:33:49.554945Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-10T02:53:29.245217Z

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 f88576ce-6631-4c0b-a354-906d77d79715 · inbound

FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection cites this paper.

FastRef:Fast Prototype Refinement for Few-Shot Industrial Anomaly Detection DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T22:33:49.554945Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:33:49.554945Z digest=sha256:f7a5bdd49356e15f3c7e627f6e422849dffad8ed293b2cc7630ff0c64429cdc3

Observation 68f26e52-1234-445d-8fd8-2c9fa9c35e20 · inbound

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network cites this paper.

Industrial Surface Defect Detection via Diffusion Generation and Asymmetric Student-Teacher Network DiAD: A Diffusion-based Framework for Multi-class Anomaly Detection

Reference 33

Resolution
verified exact
arxiv_id, observed 2026-05-10T02:53:29.246596Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T02:52:57.713567Z digest=sha256:413e31caa944402e761713463c176d1f6e3beb33a6805b76a7b130d8d9636edc