Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Large Language Models for Network Intrusion Detection Systems: Foundations, Implementations, and Future Directions
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2507.04752.
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 2026-08-05T06:32:48.257954+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-07-13T09:28:30.950169Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-10T22:30:52.969938Z
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 bc688e87-918b-463e-8e81-a104e3646f46 · inbound
MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library cites this paper.
MA-IDS: Multi-Agent RAG Framework for IoT Network Intrusion Detection with an Experience Library Large Language Models for Network Intrusion Detection Systems: Foundations, Implementations, and Future Directions
Reference 4
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T22:30:52.974912Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.
Observation 2fdfb8d3-b22c-4e38-ac92-302944068966 · inbound
SMT-AD: a scalable quantum-inspired anomaly detection approach cites this paper.
SMT-AD: a scalable quantum-inspired anomaly detection approach Large Language Models for Network Intrusion Detection Systems: Foundations, Implementations, and Future Directions
Reference 31
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T09:28:30.950169Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 193aa1b4-7359-44de-abc7-a1e7d6e5c4c6 · inbound
Attribution-Driven Explainable Intrusion Detection with Encoder-Based Large Language Models cites this paper.
Attribution-Driven Explainable Intrusion Detection with Encoder-Based Large Language Models Large Language Models for Network Intrusion Detection Systems: Foundations, Implementations, and Future Directions
Reference 31
- Resolution
- verified exact
- arxiv_id, observed 2026-05-10T22:15:48.791017Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.