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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 2026-08-22T06:32:14.747728+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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T10:19:47.705438Z digest=sha256:0a920e70b353145111069c444e3d036d6b617fb2e9789ec45d32b1060e9a0ede

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T10:19:47.710773Z digest=sha256:80c318010335525793e78dbeba12bcc53c2d7e88f83f0a784ee6631038c90617

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T10:19:47.715462Z digest=sha256:d2182287f5bfc906ed99a136801d0a28c472648e6163c3d7bc7da398d0bb4659

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.

source=pdf_text observed=2026-08-16T10:19:47.720098Z digest=sha256:a13c56b21fce3f807cb886142e16e132e1d9aa2e30f7cffa1a04029d0e1aee50

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T10:19:47.730529Z digest=sha256:bcc4d03333e23ea7447554c4a937618b842c61feca3d4a9514e41b5f35da0994

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.

source=pdf_text observed=2026-08-16T10:19:47.735776Z digest=sha256:019e29f90e28e5e7fbb57e5d3ba5352f43d65cec21dd2ec991837749f7bfb6be

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.

source=pdf_text observed=2026-08-16T10:19:47.740204Z digest=sha256:9374210806b4f77ee3afd878da80259fd0e3c565c5fd5fc326acf1b9fc7077d5

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.

source=pdf_text observed=2026-08-16T10:19:47.744800Z digest=sha256:a8c0f634fa2349b38b12ec19e363aba0b12cd3b410305e05ef39ad62bf15e3ca

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.

source=pdf_text observed=2026-08-16T10:19:47.749832Z digest=sha256:936c666d2b8526d591ea2038bfb38ba86162b13f06e14ca7edb1cc2ac34f402c

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T10:19:47.754659Z digest=sha256:2ef93c512f18b938172177ef4e9bd59d7fba1b4ee6e138ecc90a803ab5c8a2ff

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T10:19:47.760032Z digest=sha256:ea5185a0d20fc3c5ced770c2121b1af83296f310954129079b6a478ad3adc205

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 2026-08-22T06:32:14.747728+00:00.

source=pdf_text observed=2026-08-16T10:19:47.765057Z digest=sha256:7bd6d1205655fc895de03fecf369e93c6a7f3760b000b119bd215bd563b2d5e4

Pith citing papers

No inbound Pith citation observations are available.