Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Benchmarking Large Language Models for Log Analysis, Security, and Interpretation
As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2311.14519.
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 2026-08-18T06:34:40.430872+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-09T22:42:57.599811Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-15T01:03:25.231682Z
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 06a90055-ee09-48ac-b039-2cf6687ad00b · inbound
Evaluating Large Language Models in Vulnerability Detection Under Variable Context Windows cites this paper.
Evaluating Large Language Models in Vulnerability Detection Under Variable Context Windows Benchmarking Large Language Models for Log Analysis, Security, and Interpretation
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-09T22:42:57.599811Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1144be08-4416-4a07-ab56-894652fb4960 · inbound
Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques cites this paper.
Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Benchmarking Large Language Models for Log Analysis, Security, and Interpretation
Reference 106
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T16:24:30.001174Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 746e5e06-5a3c-425e-9eff-6477b060e73c · inbound
Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage cites this paper.
Policy-Guided Threat Hunting: An LLM enabled Framework with Splunk SOC Triage Benchmarking Large Language Models for Log Analysis, Security, and Interpretation
Reference 33
- Resolution
- verified exact
- arxiv_id, observed 2026-05-15T01:03:25.233110Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.