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Paper Citation Record · LEDGER

Examining Zero-Shot Vulnerability Repair with Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2112.02125.

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

pith.paper-citation-record.v1
2112.02125 v3

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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:24:29.807345Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T04:06:34.801261Z

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 8c7a3e7e-e4e6-4925-8c24-1944605d8247 · inbound

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques cites this paper.

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Examining Zero-Shot Vulnerability Repair with Large Language Models

Reference 75

Resolution
unresolved
no resolver link, observed 2026-08-06T16:24:29.807345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:24:29.807345Z digest=sha256:802ce8bfe364212cce2af191748d8b87c74bfb1d952fa98b28a6d6163720605a

Observation 5755a020-45f7-4c74-9031-78710466a1ee · inbound

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

Characterizing initial human-AI proof formalization workflows Examining Zero-Shot Vulnerability Repair with Large Language Models

Reference 105

Resolution
verified exact
arxiv_id, observed 2026-07-02T04:06:34.802806Z

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.

source=arxiv_source observed=2026-06-28T09:29:50.282874Z digest=sha256:8ee41df4733dc7271ace63650b1cd107cf628c9f152c6bb7c8b185587553dc30