Pith. sign in

Paper Citation Record · LEDGER

DMAD: Dual Memory Bank for Real-World Anomaly Detection

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2403.12362.

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

pith.paper-citation-record.v1
2403.12362 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T14:10:33.979154Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:15:03.946401Z

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 f7c8900e-ea7f-4645-9155-9333dea0b927 · inbound

SuperAD: A Training-free Anomaly Classification and Segmentation Method for CVPR 2025 VAND 3.0 Workshop Challenge Track 1: Adapt & Detect cites this paper.

SuperAD: A Training-free Anomaly Classification and Segmentation Method for CVPR 2025 VAND 3.0 Workshop Challenge Track 1: Adapt & Detect DMAD: Dual Memory Bank for Real-World Anomaly Detection

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-07T14:10:33.979154Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T14:10:33.979154Z digest=sha256:46a893e94465ae1f521b8f029c3edb900b043e3a624448497ef9c2a5dddfb305

Observation 940d25b7-21ee-4820-9c72-1d171d22a413 · inbound

SuperADD: Training-free Class-agnostic Anomaly Segmentation -- CVPR 2026 VAND 4.0 Workshop Challenge Industrial Track cites this paper.

SuperADD: Training-free Class-agnostic Anomaly Segmentation -- CVPR 2026 VAND 4.0 Workshop Challenge Industrial Track DMAD: Dual Memory Bank for Real-World Anomaly Detection

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-30T21:15:03.948274Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T21:14:49.787243Z digest=sha256:2d97deb694abcf08ca22bb8505b0e77031ba59155a9753809a2d9acb72a847b2