Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2412.03342.
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 2026-08-07T15:01:02.377695Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T17:22:04.608717Z
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 f3f8baed-4996-4f75-9856-f61f16d89af0 · inbound
SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images cites this paper.
SD-MAD: Sign-Driven Few-shot Multi-Anomaly Detection in Medical Images UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T15:01:02.377695Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 79c5195f-752d-4012-8bd2-2fda2e600cc3 · inbound
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning cites this paper.
OmniAD: Detect and Understand Industrial Anomaly via Multimodal Reasoning UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:20:58.812195Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 273c508f-5850-446d-81b3-ab619fd6baa8 · inbound
A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects cites this paper.
A Comprehensive Survey for Real-World Industrial Defect Detection: Challenges, Approaches, and Prospects UniVAD: A Training-free Unified Model for Few-shot Visual Anomaly Detection
Reference 177
- Resolution
- verified exact
- local_arxiv, observed 2026-08-06T17:22:04.715160Z
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.