Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2504.06740.
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 2026-08-20T06:33:59.587034+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T17:28:41.985485Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T13:56:59.025955Z
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 e374e0fd-461a-484d-b874-4228f5a1ddcb · inbound
Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation cites this paper.
Defect-aware Hybrid Prompt Optimization via Progressive Tuning for Zero-Shot Multi-type Anomaly Detection and Segmentation MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
Reference 28
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T17:28:41.985485Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e8839262-3e57-4873-a4d3-fb6868cf3c2d · inbound
GS-CLIP: Zero-shot 3D Anomaly Detection by Geometry-Aware Prompt and Synergistic View Representation Learning cites this paper.
GS-CLIP: Zero-shot 3D Anomaly Detection by Geometry-Aware Prompt and Synergistic View Representation Learning MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T21:46:33.221125Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0f0e1a38-b9eb-46e3-aa90-0c2e5c849e57 · 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 MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T11:55:33.300289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.
Observation 82f80d42-591a-459b-a3a4-6fe1cf91c0ba · inbound
GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models cites this paper.
GenAU: Language-Grounded Industrial Anomaly Understanding with Vision-Language Models MultiADS: Defect-aware Supervision for Multi-type Anomaly Detection and Segmentation in Zero-Shot Learning
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T13:56:59.027667Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.