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Paper Citation Record · LEDGER

COFT-AD: COntrastive Fine-Tuning for Few-Shot 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:2402.18998.

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

pith.paper-citation-record.v1
2402.18998 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 2026-08-05T19:03:29.476048Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T18:59:10.164592Z

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 aacabae7-a46f-4a0e-9444-032444009acc · inbound

DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup cites this paper.

DictAS: A Framework for Class-Generalizable Few-Shot Anomaly Segmentation via Dictionary Lookup COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection

Reference 22

Resolution
verified exact
local_arxiv, observed 2026-08-05T18:59:10.303460Z

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=arxiv_source observed=2026-08-05T18:59:08.451570Z digest=sha256:912c02e771a1748df5263858288e8013e2f7b3baa56fbe52f22eaf41f0586692

Observation 7511df04-42a8-46ba-b4f3-55365d741126 · inbound

Generative Model-Based Feature Attention Module for Video Action Analysis cites this paper.

Generative Model-Based Feature Attention Module for Video Action Analysis COFT-AD: COntrastive Fine-Tuning for Few-Shot Anomaly Detection

Reference 21

Resolution
unresolved
no resolver link, observed 2026-08-05T19:03:29.476048Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-05T19:03:29.476048Z digest=sha256:734573f549bf6dc345cfdb4efd67a4cf899309acf34467305250b9c975d2949e