Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2409.10756.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-12T19:14:49.304233Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-23T02:22:24.825173Z
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 32d32ffa-27a8-4efe-b084-0fa307655715 · inbound
INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection cites this paper.
INVARLLM: LLM-assisted Physical Invariant Extraction for Cyber-Physical Systems Anomaly Detection VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 58
- Resolution
- unresolved
- no resolver link, observed 2026-08-12T19:14:49.304233Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 44d6dbbb-a1e7-4fba-8408-a2d01bcf52b4 · inbound
BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos cites this paper.
BioPose: Biomechanically-accurate 3D Pose Estimation from Monocular Videos VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 42
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T20:41:24.481294Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 18d5bb3a-3c95-41ae-b6e6-3f7adfe8080d · inbound
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights cites this paper.
LLMs in Software Security: A Survey of Vulnerability Detection Techniques and Insights VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 147
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:58:14.291172Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation c70f8081-f46f-4124-9220-a17ca0813096 · inbound
Cyber-Physical Systems Security: A Comprehensive Review of Anomaly Detection Techniques cites this paper.
Cyber-Physical Systems Security: A Comprehensive Review of Anomaly Detection Techniques VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 103
- Resolution
- verified exact
- arxiv_id, observed 2026-05-23T02:22:24.831973Z
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.
Observation d602f9b2-5727-45ab-af54-b1d4edaa3aeb · inbound
Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond cites this paper.
Mono: Is Your "Clean" Vulnerability Dataset Really Solvable? Exposing and Trapping Undecidable Patches and Beyond VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 17
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T11:01:16.109869Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b232112c-ba2f-4f62-8619-9e8877a6cdc2 · inbound
QuiLL: An LLM-Based Vulnerability Assessment Framework for the Wild cites this paper.
QuiLL: An LLM-Based Vulnerability Assessment Framework for the Wild VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 19
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T11:01:17.204575Z
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.
Observation 20fdc60a-7ae9-4e87-a93f-6ded15a5b05f · inbound
Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics cites this paper.
Program Structure-aware Language Models: Targeted Software Testing beyond Textual Semantics VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 45
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-10T09:48:47.990857Z
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.
Observation 8c60e637-d752-4732-9634-9a4b84c9063e · inbound
Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection cites this paper.
Three Heads Are Better Than One: A Multi-perspective Reasoning Framework for Enhanced Vulnerability Detection VulnLLMEval: A Framework for Evaluating Large Language Models in Software Vulnerability Detection and Patching
Reference 77
- Resolution
- verified exact
- arxiv_id, observed 2026-05-20T09:18:10.100385Z
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.