Paper Citation Record · LEDGER

Is GitHub's Copilot as Bad as Humans at Introducing Vulnerabilities in Code?

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2204.04741.

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

pith.paper-citation-record.v1
2204.04741 v5

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T19:34:34.465464Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T04:06:34.869804Z

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 c3c039e5-f7aa-415d-b320-91a23c29485b · inbound

A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT cites this paper.

A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT Is GitHub's Copilot as Bad as Humans at Introducing Vulnerabilities in Code?

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T07:09:16.862754Z

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 0e400457-aa89-468c-887b-2c12dd13c256 · inbound

In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code cites this paper.

In-Context Learning as an Effective Estimator of Functional Correctness of LLM-Generated Code Is GitHub's Copilot as Bad as Humans at Introducing Vulnerabilities in Code?

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-06T19:34:34.465464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2d266784-f005-4787-b930-8cc519f1a7d2 · inbound

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code cites this paper.

Bridging Generation and Training: A Systematic Review of Quality Issues in LLMs for Code Is GitHub's Copilot as Bad as Humans at Introducing Vulnerabilities in Code?

Reference 7

Resolution: verified exact; arxiv_id, observed 2026-05-11T17:26:04.614584Z

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 f1e7397d-63c8-410b-823e-1faffff2e36e · inbound

Characterizing initial human-AI proof formalization workflows cites this paper.

Characterizing initial human-AI proof formalization workflows Is GitHub's Copilot as Bad as Humans at Introducing Vulnerabilities in Code?

Reference 186

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T04:06:34.871167Z

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.