Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2405.07626.
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 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T16:34:14.331763Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-30T20:05:04.418878Z
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 6bb610b5-bb50-4b6e-bf17-4e769ed8e204 · inbound
Foundation Models for Anomaly Detection: Vision and Challenges cites this paper.
Foundation Models for Anomaly Detection: Vision and Challenges AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:34:14.331763Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5e8af14d-ae62-4b5e-be72-4542ff9d5525 · inbound
A Survey of AIOps in the Era of Large Language Models cites this paper.
A Survey of AIOps in the Era of Large Language Models AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Reference 76
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:26:36.775514Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a6d12069-524b-4a7c-b8cf-88aec7f4fc0f · inbound
Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thought cites this paper.
Adaptive Root Cause Localization for Microservice Systems with Multi-Agent Recursion-of-Thought AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-05T15:10:28.372375Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 908a880e-1361-488d-ba26-234f4bc51775 · inbound
E2E-REME: Towards End-to-End Microservices Auto-Remediation via Experience-Simulation Reinforcement Fine-Tuning cites this paper.
E2E-REME: Towards End-to-End Microservices Auto-Remediation via Experience-Simulation Reinforcement Fine-Tuning AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T10:25:59.315711Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.
Observation 5350de15-3980-4dae-85ac-a80fd067747d · inbound
Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought cites this paper.
Towards In-Depth Root Cause Localization for Microservices with Multi-Agent Recursion-of-Thought AnomalyLLM: Few-shot Anomaly Edge Detection for Dynamic Graphs using Large Language Models
Reference 82
- Resolution
- verified exact
- arxiv_id, observed 2026-06-30T20:05:04.420289Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.