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Paper Citation Record · LEDGER

Vulnerability Handling of AI-Generated Code -- Existing Solutions and Open Challenges

As of 13 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2408.08549.

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

pith.paper-citation-record.v1
2408.08549 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T16:10:34.524900Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-11T01:04:04.019216Z

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 fe390531-5094-4b2d-8bab-72d6588a7e54 · inbound

Applied Statistics in the Era of Artificial Intelligence: A Review and Vision cites this paper.

Applied Statistics in the Era of Artificial Intelligence: A Review and Vision Vulnerability Handling of AI-Generated Code -- Existing Solutions and Open Challenges

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-11T16:10:34.524900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T16:10:34.524900Z digest=sha256:0ef950c3626cdf74c1d29705f9ca5ad9fc51a939e03ad9c28b4baae6eb5cd396

Observation 08cafb2d-6691-48e3-8983-fca985485e3f · inbound

How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study cites this paper.

How Propense Are Large Language Models at Producing Code Smells? A Benchmarking Study Vulnerability Handling of AI-Generated Code -- Existing Solutions and Open Challenges

Reference 11

Resolution
verified exact
local_arxiv, observed 2026-08-11T01:04:04.024541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-13T06:32:02.005865+00:00.

source=pdf_text observed=2026-08-11T01:04:03.454292Z digest=sha256:87cbc80373dbe70acaa5ace626156b35a545cf4639452e6b4925dc494767b143