Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
As of 15 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2303.14814.
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 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T20:51:59.952143Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-16T03:07:11.908089Z
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 0db2ef9f-7144-4901-82fa-ca71d3455b27 · inbound
Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet? cites this paper.
Exploring Zero-Shot Anomaly Detection with CLIP in Medical Imaging: Are We There Yet? WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T20:51:59.952143Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 2866a241-abb5-4332-b2b3-eaf3576542aa · inbound
PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments cites this paper.
PB-IAD: Utilizing multimodal foundation models for semantic industrial anomaly detection in dynamic manufacturing environments WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T18:34:07.112109Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 46baf02a-7eda-435e-b536-ab970832e967 · inbound
HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection cites this paper.
HLGFA: High-Low Resolution Guided Feature Alignment for Unsupervised Anomaly Detection WinCLIP: Zero-/Few-Shot Anomaly Classification and Segmentation
Reference 8
- Resolution
- verified exact
- arxiv_id, observed 2026-05-16T03:07:11.911580Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-15T06:32:42.880941+00:00.