Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2403.19735.
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 2026-08-08T19:23:59.932797Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T13:21:19.486771Z
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 16e68075-cab8-4ac9-b56a-e3d13e94d844 · inbound
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews cites this paper.
Agentic AI Systems Applied to tasks in Financial Services: Modeling and model risk management crews Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T19:23:59.932797Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 28cf7d61-4070-4217-8474-f8a409d8c68e · inbound
Foundation Models for Anomaly Detection: Vision and Challenges cites this paper.
Foundation Models for Anomaly Detection: Vision and Challenges Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T16:34:14.350074Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 650d9a0c-0d9f-4f6c-ae07-58e1133f2525 · inbound
Building crypto portfolios with agentic AI cites this paper.
Building crypto portfolios with agentic AI Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework
Reference 10
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T18:14:06.604780Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0d43f1b2-086b-4da8-b113-a04c60eb29da · inbound
Enhancing Tabular Anomaly Detection via Pseudo-Label-Guided Generation cites this paper.
Enhancing Tabular Anomaly Detection via Pseudo-Label-Guided Generation Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework
Reference 2
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-11T12:16:05.390762Z
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.
Observation f75151e7-3dc8-41a9-af41-26362d4febd7 · inbound
Integrating Anomaly Detection into Agentic AI for Proactive Risk Management in Human Activity cites this paper.
Integrating Anomaly Detection into Agentic AI for Proactive Risk Management in Human Activity Enhancing Anomaly Detection in Financial Markets with an LLM-based Multi-Agent Framework
Reference 11
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T13:21:19.489842Z
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.