Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language Model
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.00556.
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 2026-08-06T17:29:56.288957Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T14:20:30.582663Z
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 fd88ed37-f2a7-497e-82d0-64acd31024f0 · inbound
From Alerts to Intelligence: A Novel LLM-Aided Framework for Host-based Intrusion Detection cites this paper.
From Alerts to Intelligence: A Novel LLM-Aided Framework for Host-based Intrusion Detection FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language Model
Reference 18
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:29:56.288957Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5ae3d3fc-82f2-40d8-9b1a-619b655e618e · inbound
PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios cites this paper.
PostureObjectstitch: Anomaly Image Generation Considering Assembly Relationships in Industrial Scenarios FADE: Few-shot/zero-shot Anomaly Detection Engine using Large Vision-Language Model
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T14:20:30.586080Z
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.