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Paper Citation Record · LEDGER

LLbezpeky: Leveraging Large Language Models for Vulnerability Detection

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2401.01269.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2401.01269 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:32:23.511479Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

11
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 88edbe16-2436-4a83-8e2c-76de19ae7767 · 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 LLbezpeky: Leveraging Large Language Models for Vulnerability Detection

Reference 49

Resolution
verified exact
arxiv_id, observed 2026-05-23T06:52:39.669608Z

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.

source=pdf_text observed=2026-05-23T06:51:09.608735Z digest=sha256:34a42ae4af67f8d588f6ba31934c2d16a3ab96cf66ccbb5296e6337f16a787ab

Observation 0ab3ab3f-c434-4820-90c1-fe8240e8a36e · inbound

LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights cites this paper.

LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights LLbezpeky: Leveraging Large Language Models for Vulnerability Detection

Reference 86

Resolution
unresolved
no resolver link, observed 2026-08-08T13:58:14.011152Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T13:58:14.011152Z digest=sha256:db31460999dfdf2cec6026b2dc764b56e866c13641f0278f8d0990586f0ddb95

Observation 6c57bc83-78d5-451d-826c-34d49749b39d · inbound

A Contemporary Survey of Large Language Model Assisted Program Analysis cites this paper.

A Contemporary Survey of Large Language Model Assisted Program Analysis LLbezpeky: Leveraging Large Language Models for Vulnerability Detection

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-09T05:32:23.511479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-09T05:32:23.511479Z digest=sha256:c7a5bacc215acce3666a4ece95af0b85a62af477c574232cf5b376357de42848

Observation 633504f4-21d3-40b5-a11b-6dd56bed4251 · inbound

Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap cites this paper.

Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap LLbezpeky: Leveraging Large Language Models for Vulnerability Detection

Reference 31

Resolution
verified exact
arxiv_id, observed 2026-05-22T11:41:30.205287Z

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.

source=pdf_text observed=2026-05-22T11:38:16.149523Z digest=sha256:3c3d14470aeec4504566a3deea6aa538b10cd5d0e4bc32d7199996796a7907a0