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Paper Citation Record · LEDGER

Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2412.18260.

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

pith.paper-citation-record.v1
2412.18260 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 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 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:22:11.210282Z

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

1
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 4ce83898-3143-4226-a417-a45bdf8d52b6 · inbound

Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code cites this paper.

Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study

Reference 37

Resolution
verified exact
arxiv_id, observed 2026-05-22T18:41:56.394085Z

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=2026-05-22T18:40:59.564031Z digest=sha256:0e59a26a49b9f584e46bd2d6fd18806f502728477bf23fc9b9bba94e32494ea3

Observation 709a49c8-a7b6-47ae-a80a-b3d99e8bdf4e · inbound

SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code cites this paper.

SafeGenBench: A Benchmark Framework for Security Vulnerability Detection in LLM-Generated Code Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T10:22:11.210282Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T10:22:11.210282Z digest=sha256:1ce7e31900dc99897018c68635eaab4e40b9e900011c83ba9c1238effd1359bd

Observation c684e588-e813-41df-afef-e82c1ea17900 · inbound

ZoFia: Zero-Shot Fake News Detection with Entity-Guided Retrieval and Multi-LLM Interaction cites this paper.

ZoFia: Zero-Shot Fake News Detection with Entity-Guided Retrieval and Multi-LLM Interaction Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-05-18T01:50:38.232601Z

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=arxiv_source observed=2026-05-18T01:47:35.232468Z digest=sha256:cb78b578eaa6ef7db8cce439708cecb1493ac486f6ca8c3e8946e6780c0c7204

Observation ca3b02ec-6edf-4c41-b11c-dac3abbcd441 · 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 Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-22T11:41:30.226374Z

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=sha256:1c5c1c41f07e893dfe97f6205efcda8547ff9394f4e374e4abd7715149eec42b

Observation ccc29194-ecda-4ea5-8a02-323bb21c2c73 · inbound

How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection cites this paper.

How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study

Reference 12

Resolution
verified exact
arxiv_id, observed 2026-05-09T05:00:12.669939Z

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=2026-05-07T05:58:06.190344Z digest=sha256:5eef19c00a853090d199b00add511aa29b238b4425408e42fac5c7672ef780d5

Observation f0df35fe-2850-43a0-b72a-9dc59105d2f0 · inbound

PromptAudit: Auditing Prompt Sensitivity in LLM-Based Vulnerability Detection cites this paper.

PromptAudit: Auditing Prompt Sensitivity in LLM-Based Vulnerability Detection Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study

Reference 24

Resolution
verified exact
arxiv_id, observed 2026-06-30T16:35:12.154829Z

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=2026-06-30T16:24:55.986340Z digest=sha256:b899afe178b18da729e38f4fbd26428182551baf3ff3e7373be1bb260dd4cf40