Paper Citation Record · LEDGER

Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 24 inbound Pith citation observations for arXiv:2304.02014.

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

pith.paper-citation-record.v1
2304.02014 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 24 of 24 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T00:27:19.602826Z

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

23
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 d5fbcf98-a2f4-42d2-ada5-9e491f762fa2 · inbound

The Seeds of the FUTURE Sprout from History: Fuzzing for Unveiling Vulnerabilities in Prospective Deep-Learning Libraries cites this paper.

The Seeds of the FUTURE Sprout from History: Fuzzing for Unveiling Vulnerabilities in Prospective Deep-Learning Libraries Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-12T04:33:02.446140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b9d062d6-c717-42b7-b849-aebef1371fca · inbound

The Current Challenges of Software Engineering in the Era of Large Language Models cites this paper.

The Current Challenges of Software Engineering in the Era of Large Language Models Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T12:10:13.431433Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7fea61e7-58aa-49ee-8472-eccab263bdab · inbound

Finding Missed Code Size Optimizations in Compilers using LLMs cites this paper.

Finding Missed Code Size Optimizations in Compilers using LLMs Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-10T22:49:03.212479Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6e04e6d-0216-4d47-ba7a-c610760cd30f · inbound

A Contemporary Survey of Large Language Model Assisted Program Analysis cites this paper.

A Contemporary Survey of Large Language Model Assisted Program Analysis Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 128

Resolution: unresolved; no resolver link, observed 2026-08-09T05:32:24.558032Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fb91b21-1aac-41c0-a828-be0753c460b8 · inbound

EffiBench-X: A Multi-Language Benchmark for Measuring Efficiency of LLM-Generated Code cites this paper.

EffiBench-X: A Multi-Language Benchmark for Measuring Efficiency of LLM-Generated Code Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-15T20:26:06.043320Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation abb0ab0e-961f-4245-8bb3-78bbab86de8e · 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 Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-07T00:57:29.743159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b7b50daf-4702-4776-aa28-e8a91d4e7dd4 · inbound

Understanding LLM-Centric Challenges for Deep Learning Frameworks: An Empirical Analysis cites this paper.

Understanding LLM-Centric Challenges for Deep Learning Frameworks: An Empirical Analysis Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-07T00:41:10.949366Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 91d2763f-2619-43ef-aa60-493d5bda6ec7 · inbound

Deep Learning Framework Testing via Model Mutation: How Far Are We? cites this paper.

Deep Learning Framework Testing via Model Mutation: How Far Are We? Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-15T19:08:39.287162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fe410d96-f086-430e-bdb4-978e9e01088c · inbound

LLMCup: Ranking-Enhanced Comment Updating with LLMs cites this paper.

LLMCup: Ranking-Enhanced Comment Updating with LLMs Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T18:19:58.348487Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9fcb2cd6-c3e6-4ef4-b283-d9034425852e · 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 Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 94

Resolution: unresolved; no resolver link, observed 2026-08-06T16:24:29.922566Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b4f36b78-d7bc-454c-b966-ae36971a537d · inbound

Benchmarking LLMs for Unit Test Generation from Real-World Functions cites this paper.

Benchmarking LLMs for Unit Test Generation from Real-World Functions Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-06T10:15:37.233882Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8fa2b4c7-7de7-4029-96f3-2b5bdec4bb1b · inbound

XAMT: Cross-Framework API Matching for Testing Deep Learning Libraries cites this paper.

XAMT: Cross-Framework API Matching for Testing Deep Learning Libraries Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-05T19:30:03.977704Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4c5e8cd9-603a-4817-bdfa-30a81b8ccde1 · inbound

Pixels to Play: A Foundation Model for 3D Gameplay cites this paper.

Pixels to Play: A Foundation Model for 3D Gameplay Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T18:41:21.505449Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a75f46c9-6726-4c54-899e-3c059964828b · inbound

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing cites this paper.

MultiFuzz: A Dense Retrieval-based Multi-Agent System for Network Protocol Fuzzing Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-05T18:42:13.131228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 52789309-76b3-4809-bfe0-283577d799d7 · 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 Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-18T21:31:51.282284Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 070fccc4-dab5-4f15-af11-15890df28262 · inbound

SAGE: Semantic-Aware Gray-Box Game Regression Testing with Large Language Models cites this paper.

SAGE: Semantic-Aware Gray-Box Game Regression Testing with Large Language Models Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-03T19:29:34.205533Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9fbc410-62a1-484d-84af-c30e087cb971 · inbound

Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit cites this paper.

Like a Hammer, It Can Build, It Can Break: Large Language Model Uses, Perceptions, and Adoption in Cybersecurity Operations on Reddit Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T08:16:01.224264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation b43e6cd0-1002-445d-a29b-af2da3a67fd7 · inbound

TEMPLATEFUZZ: Fine-Grained Chat Template Fuzzing for Jailbreaking and Red Teaming LLMs cites this paper.

TEMPLATEFUZZ: Fine-Grained Chat Template Fuzzing for Jailbreaking and Red Teaming LLMs Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:26:00.023299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 42fa8c1b-8487-40a3-8524-b77be80c159c · inbound

SDLLMFuzz: Dynamic-static LLM-assisted greybox fuzzing for structured input programs cites this paper.

SDLLMFuzz: Dynamic-static LLM-assisted greybox fuzzing for structured input programs Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:23:37.625713Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 747246f6-b5f2-4cea-9213-ecb00a35c78a · inbound

ClozeMaster: Fuzzing Rust Compiler by Harnessing LLMs for Infilling Masked Real Programs cites this paper.

ClozeMaster: Fuzzing Rust Compiler by Harnessing LLMs for Infilling Masked Real Programs Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-11T15:41:07.706376Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation c737f2b1-a73f-4f24-a12f-4149087a44a3 · inbound

ParityFuzz: Finding Inconsistencies across Solidity Compilers via Fine-Grained Mutation and Differential Analysis cites this paper.

ParityFuzz: Finding Inconsistencies across Solidity Compilers via Fine-Grained Mutation and Differential Analysis Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-05-12T07:36:36.274681Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

Observation 65df4667-36b9-4a35-ad16-da6d3c5b7efc · inbound

When Fuzzing Meets Understanding: LLM-Driven Semantic Test Generation for RTL Verification cites this paper.

When Fuzzing Meets Understanding: LLM-Driven Semantic Test Generation for RTL Verification Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 11

Resolution: unresolved; no resolver link, observed 2026-07-14T12:30:31.318373Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2681f208-a38d-4d07-af4b-6c672ebd3556 · inbound

GapForge: Directed Compiler Fuzzing via Coverage-Gap Analysis cites this paper.

GapForge: Directed Compiler Fuzzing via Coverage-Gap Analysis Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-01T22:26:30.437114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 79ca9aa8-30a0-48f7-8804-54fa869d8494 · inbound

Testing Deep Learning Library APIs via Cross-Framework Differential Fuzzing cites this paper.

Testing Deep Learning Library APIs via Cross-Framework Differential Fuzzing Large Language Models are Edge-Case Fuzzers: Testing Deep Learning Libraries via FuzzGPT

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T00:27:19.602826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.