Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T14:10:33.979154Z
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.
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 2026-08-08T06:32:00.761636+00:00.