Paper Citation Record · LEDGER

Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2212.14834.

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

pith.paper-citation-record.v1
2212.14834 v4

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 2026-08-07T00:57:28.748900Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

13
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 3cdbd95b-c5d3-416d-8498-8594cd2d7363 · inbound

The Foundation Cracks: A Comprehensive Study on Bugs and Testing Practices in LLM Libraries cites this paper.

The Foundation Cracks: A Comprehensive Study on Bugs and Testing Practices in LLM Libraries Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-07T00:57:28.748900Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0bc14439-3f4b-42d1-b66e-463087c1f26d · inbound

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

Large Language Models in Cybersecurity: Applications, Vulnerabilities, and Defense Techniques Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.910973Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 291bf0ee-6e08-4c11-9ec2-22f33d70681a · inbound

Once4All: Skeleton-Guided SMT Solver Fuzzing with LLM-Synthesized Generators cites this paper.

Once4All: Skeleton-Guided SMT Solver Fuzzing with LLM-Synthesized Generators Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-18T21:31:51.293352Z

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 33083ac4-a8bf-46dc-b92e-1ad0319054f7 · inbound

ViBR: Automated Bug Replay from Video-based Reports using Vision-Language Models cites this paper.

ViBR: Automated Bug Replay from Video-based Reports using Vision-Language Models Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-11T13:21:07.015791Z

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 3bbac52f-aaab-490c-9069-65d59a8847c3 · inbound

ConcoLixir: Reactive LLM Discovery Oracles for Python Concolic Testing cites this paper.

ConcoLixir: Reactive LLM Discovery Oracles for Python Concolic Testing Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-06-26T05:09:00.780008Z

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 6e8247db-cce2-46b3-b0ee-7df30300e8ea · inbound

From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs cites this paper.

From Resource Flow to Executable Tests: Petri-Net-Guided LLM Test Generation for Concurrent Stateful Rust APIs Large Language Models are Zero-Shot Fuzzers: Fuzzing Deep-Learning Libraries via Large Language Models

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-01T07:12:18.071034Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.