Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2403.14213.
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 2026-08-06T05:05:24.187070Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T21:06:38.112966Z
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 669cb13f-7e8d-4157-98ed-dcf5cb86c366 · inbound
Multi-class Image Anomaly Detection for Practical Applications: Requirements and Robust Solutions cites this paper.
Multi-class Image Anomaly Detection for Practical Applications: Requirements and Robust Solutions Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference
Reference 11
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T05:05:24.187070Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e60ccdee-a161-4f8d-847d-1cccf9a67b17 · inbound
EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models cites this paper.
EAGLE: Expert-Augmented Attention Guidance for Tuning-Free Industrial Anomaly Detection in Multimodal Large Language Models Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T21:06:38.117756Z
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.
Observation 967b8cc7-823e-4cb5-a24b-ce8423866373 · inbound
AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparison cites this paper.
AD-Copilot: A Vision-Language Assistant for Industrial Anomaly Detection via Visual In-context Comparison Toward Multi-class Anomaly Detection: Exploring Class-aware Unified Model against Inter-class Interference
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T11:55:33.357040Z
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.