Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2401.16753.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:27:16.090916Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-06T15:32:53.960530Z
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 39d5fbe3-e170-4c0c-b46f-b9a828cbc12e · inbound
Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection cites this paper.
Bridge Feature Matching and Cross-Modal Alignment with Mutual-filtering for Zero-shot Anomaly Detection MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:27:16.090916Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation eb5121ef-57d5-46a6-9aee-d077c0999345 · 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 MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images
Reference 188
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:21:51.565340Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3cbfde70-e9c0-42da-8236-5096c636530e · inbound
Foundation Models and Transformers for Anomaly Detection: A Survey cites this paper.
Foundation Models and Transformers for Anomaly Detection: A Survey MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images
Reference 2025
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-08-06T15:32:53.965219Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.