Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2405.15614.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T23:41:46.609494Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T06:52:39.957839Z
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 8cb19f96-35bb-4823-bfea-0790371651a9 · inbound
Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points cites this paper.
Direction for Detection: A Survey of Automated Vulnerability Detection and all of its Pain Points Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study
Reference 155
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T06:52:39.960972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.
Observation 8b998abd-7367-4d69-a07a-79415f5c721c · inbound
Towards Effective Complementary Security Analysis using Large Language Models cites this paper.
Towards Effective Complementary Security Analysis using Large Language Models Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T23:41:46.609494Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 12ac03a4-cbf6-42b0-9f0e-1e6768c6a4a1 · inbound
Analyzing the Instability of Large Language Models in Automated Bug Injection and Correction cites this paper.
Analyzing the Instability of Large Language Models in Automated Bug Injection and Correction Harnessing Large Language Models for Software Vulnerability Detection: A Comprehensive Benchmarking Study
Reference 23
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T23:41:28.794992Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.