Paper Citation Record · LEDGER

How Far Have We Gone in Vulnerability Detection Using Large Language Models

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 14 inbound Pith citation observations for arXiv:2311.12420.

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

pith.paper-citation-record.v1
2311.12420 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 14 of 14 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 14 of 14 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T14:24:49.785110Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T04:29:35.021853Z

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 86201560-bb4a-44db-bd6b-23225ffce660 · 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 How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 143

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:52:40.023775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation a78bd7c0-830e-4deb-8ada-16ce2d116f35 · inbound

Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection cites this paper.

Can LLM Prompting Serve as a Proxy for Static Analysis in Vulnerability Detection How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-11T14:24:49.785110Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5512ed37-385a-4ec4-b862-8404a54982d0 · inbound

Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study cites this paper.

Investigating Large Language Models for Code Vulnerability Detection: An Experimental Study How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-11T04:55:44.873435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a05018bc-fe92-40bb-85a9-6fe1998aba49 · 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 How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-08T13:58:13.791321Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49a6a00d-cc12-427a-9205-56f9112b51ae · inbound

ReCopilot: Reverse Engineering Copilot in Binary Analysis cites this paper.

ReCopilot: Reverse Engineering Copilot in Binary Analysis How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T15:06:37.721294Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1d94e7e7-ec78-4e94-8bec-bee094aa61f1 · inbound

LPASS: Linear Probes as Stepping Stones for vulnerability detection using compressed LLMs cites this paper.

LPASS: Linear Probes as Stepping Stones for vulnerability detection using compressed LLMs How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-07T12:29:16.692942Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b536cd7-2183-4285-a76d-e6d0ca2c4941 · inbound

Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond cites this paper.

Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-07T11:01:16.196105Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8e153b3b-cf27-45dd-9f3f-4cf8fdfec779 · inbound

Measuring and Augmenting Large Language Models for Solving Capture-the-Flag Challenges cites this paper.

Measuring and Augmenting Large Language Models for Solving Capture-the-Flag Challenges How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-06T23:35:03.441508Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8c9976c4-f52b-4ba9-b482-0afb4f9be606 · inbound

QuiLL: An LLM-Based Vulnerability Assessment Framework for the Wild cites this paper.

QuiLL: An LLM-Based Vulnerability Assessment Framework for the Wild How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-05-18T11:01:17.210682Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 92e5d328-6bcf-4a93-8b63-85d65665a01f · inbound

XekRung Technical Report cites this paper.

XekRung Technical Report How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 86

Resolution: metadata mismatch; arxiv_id, observed 2026-05-11T14:51:14.709906Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 5bf3f5f8-fa15-43a8-94da-fd3be4909b02 · inbound

Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection cites this paper.

Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-20T09:18:10.073951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b295eed7-eaf6-4af5-8249-d9f845b93df3 · inbound

Calibration Without Comprehension: Diagnosing the Limits of Fine-Tuning LLMs for Vulnerability Detection in Systems Software cites this paper.

Calibration Without Comprehension: Diagnosing the Limits of Fine-Tuning LLMs for Vulnerability Detection in Systems Software How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 16

Resolution: verified exact; arxiv_id, observed 2026-07-04T04:29:35.023976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation b5792506-081d-4e5b-9d25-6398393f95b3 · inbound

OASIF: An Efficient Obfuscation-Aware Self-Improving Framework for LLM-Based Assembly Code Instruction Following and Comprehension cites this paper.

OASIF: An Efficient Obfuscation-Aware Self-Improving Framework for LLM-Based Assembly Code Instruction Following and Comprehension How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-06-30T03:04:13.890078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation fac6c4af-ecbd-45f8-8f14-fd0ffc3e38e4 · inbound

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection cites this paper.

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection How Far Have We Gone in Vulnerability Detection Using Large Language Models

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-30T04:54:16.791134Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.