Paper Citation Record · LEDGER

Evaluation of ChatGPT Model for Vulnerability Detection

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2304.07232.

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

pith.paper-citation-record.v1
2304.07232 v1

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 2026-08-08T17:26:43.388996Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T06:52:39.977745Z

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 3bf500e9-fcad-4780-92d1-c94b81be5ae1 · 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 Evaluation of ChatGPT Model for Vulnerability Detection

Reference 157

Resolution: verified exact; arxiv_id, observed 2026-05-23T06:52:39.980173Z

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.

Observation 57052080-a851-48fd-9378-921ce0f8f236 · inbound

Large Language Models for In-File Vulnerability Localization Can Be "Lost in the End" cites this paper.

Large Language Models for In-File Vulnerability Localization Can Be "Lost in the End" Evaluation of ChatGPT Model for Vulnerability Detection

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-08T17:26:43.388996Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 991c20e0-8993-40c1-b5f7-794dc69a079f · inbound

An Initial Exploration of Fine-tuning Small Language Models for Smart Contract Reentrancy Vulnerability Detection cites this paper.

An Initial Exploration of Fine-tuning Small Language Models for Smart Contract Reentrancy Vulnerability Detection Evaluation of ChatGPT Model for Vulnerability Detection

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T14:24:44.358751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dbc61c80-be9b-4462-a8f2-f3e0fdd7bdff · inbound

LLM Embedding-based Attribution (LEA): Quantifying Source Contributions to Generative Model's Response for Vulnerability Analysis cites this paper.

LLM Embedding-based Attribution (LEA): Quantifying Source Contributions to Generative Model's Response for Vulnerability Analysis Evaluation of ChatGPT Model for Vulnerability Detection

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-07T04:19:09.055205Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c6b7d6e-2e75-42f3-988e-bfb76d2c769a · inbound

Large Language Models for Security Operations Centers: A Comprehensive Survey cites this paper.

Large Language Models for Security Operations Centers: A Comprehensive Survey Evaluation of ChatGPT Model for Vulnerability Detection

Reference 256

Resolution: unresolved; no resolver link, observed 2026-08-04T17:32:21.563272Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d0793d5a-e6be-48d5-afb7-c5eef46aaac1 · inbound

QASecClaw: A Multi-Agent LLM Approach for False Positive Reduction in Static Application Security Testing cites this paper.

QASecClaw: A Multi-Agent LLM Approach for False Positive Reduction in Static Application Security Testing Evaluation of ChatGPT Model for Vulnerability Detection

Reference 28

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:26:03.489601Z

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.