Paper Citation Record · LEDGER

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection

As of 22 August 2026, this Paper Citation Record lists 12 of 12 outbound references and 0 inbound Pith citation observations for arXiv:2504.18423.

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

pith.paper-citation-record.v1
2504.18423 v1

Coverage vector

measured 12 of 12 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T10:19:47.765057Z

measured 12 of 12 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

12 of 12 outbound references displayed

verified exact1
verified fuzzy6
unresolved5
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation afb415f6-96cc-4f7c-baca-2589086a9c18 · outbound

This paper cites We analysed 90,000+ software vulnerabilities: Here’s what we learned,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection We analysed 90,000+ software vulnerabilities: Here’s what we learned,

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:47.975789Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 9ea820fa-a43e-4682-8b38-ab152d694faa · outbound

This paper cites Mitigating program security vulnera- bilities: Approaches and challenges,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Mitigating program security vulnera- bilities: Approaches and challenges,

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:47.958240Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 7f8ca243-1562-4662-a2b5-30bd4d2bc563 · outbound

This paper cites Out of sight, out of mind: Better automatic vulnerability repair by broadening input ranges and sources,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Out of sight, out of mind: Better automatic vulnerability repair by broadening input ranges and sources,

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:47.941779Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 23309966-e2e4-4218-9862-95bada97715d · outbound

This paper cites An empirical study of deep learning models for vulnerability detection,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection An empirical study of deep learning models for vulnerability detection,

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:47.720098Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b90ad754-4b4a-4812-8d3d-bdc6554973fc · outbound

This paper cites Human language understanding & reasoning,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Human language understanding & reasoning,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:47.915299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation a366fab6-16d0-4ff3-9bf5-4ff0270d8c32 · outbound

This paper cites Large Language Models for Software Engineering: A Systematic Literature Review.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Large Language Models for Software Engineering: A Systematic Literature Review

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:47.735776Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d2d0c596-17d8-472c-9dbc-d48b950f1e1e · outbound

This paper cites Security evaluations of github’s copilot,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Security evaluations of github’s copilot,

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:47.740204Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5f6a09bd-caf5-4604-89ec-f345c3ff6efd · outbound

This paper cites DefectHunter: A Novel LLM-Driven Boosted-Conformer-based Code Vulnerability Detection Mechanism.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection DefectHunter: A Novel LLM-Driven Boosted-Conformer-based Code Vulnerability Detection Mechanism

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:47.744800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e1f80309-f5c0-4c83-9a14-4a1d3764a6f7 · outbound

This paper cites Hallucination is Inevitable: An Innate Limitation of Large Language Models.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Hallucination is Inevitable: An Innate Limitation of Large Language Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T10:19:47.749832Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3f486a80-84df-4851-bccf-9ac1cfff8720 · outbound

This paper cites Mixture- of-agents enhances large language model capabilities,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Mixture- of-agents enhances large language model capabilities,

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:47.889419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation f2e100d0-d1ce-4c22-adda-7dcd69193bb9 · outbound

This paper cites Retrieval-augmented generation for knowledge-intensive NLP tasks,.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection Retrieval-augmented generation for knowledge-intensive NLP tasks,

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T10:19:47.873492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 768bfb8a-8960-4239-9c3e-976540e94e44 · outbound

This paper cites MOB-Net: Limb-modularized Uncertainty Torque Learning of Humanoids for Sensorless External Torque Estimation.

LLMpatronous: Harnessing the Power of LLMs For Vulnerability Detection MOB-Net: Limb-modularized Uncertainty Torque Learning of Humanoids for Sensorless External Torque Estimation

Reference 13

Resolution: verified exact; local_arxiv, observed 2026-08-16T10:19:47.809545Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Pith citing papers

No inbound Pith citation observations are available.