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Paper Citation Record · LEDGER

VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2406.07595.

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

pith.paper-citation-record.v1
2406.07595 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:03:33.764455Z

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

1
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 b9fba813-ad88-44ac-b018-df23aa2bd02b · inbound

HiLDe: Intentional Code Generation via Human-in-the-Loop Decoding cites this paper.

HiLDe: Intentional Code Generation via Human-in-the-Loop Decoding VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-07T13:03:33.764455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:03:33.764455Z digest=sha256:b1c7735411b6e32b1883df36108ff2cb55b6674a4af7c2f34c985a1922c64992

Observation 19069f42-e98b-4e82-9d9b-095ac0e0c833 · 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 VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-07T11:01:16.118464Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:01:16.118464Z digest=sha256:ffa84e89db591dcfa280eeb1da92f325c76216ff3b0fc8d8cc750b3b1faef965

Observation 225aad1e-5c95-464b-9018-e735d5372cc9 · inbound

QuiLL: An LLM-Based Vulnerability Assessment Framework for the Wild cites this paper.

QuiLL: An LLM-Based Vulnerability Assessment Framework for the Wild VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 18

Resolution
verified exact
arxiv_id, observed 2026-05-18T11:01:17.182065Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T10:56:28.973065Z digest=sha256:83a0826e302a9c8c96681910af9953a5aa60d8a1977f9e18784744ad8b2b1a64

Observation 3bfc7b60-35f8-4e8e-8cbb-633859e1ff5a · inbound

How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection cites this paper.

How Code Representation Shapes False-Positive Dynamics in Cross-Language LLM Vulnerability Detection VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-05-09T05:00:12.651412Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T05:58:06.190344Z digest=sha256:02f5579dbc4c8f9e063f2c61b72045bfa97797e2c85289052d91c46e8f741da3

Observation 02dd1c1b-5378-46f7-930b-191bc8e04dcd · inbound

Calibration Without Comprehension: Diagnosing the Limits of Fine-Tuning LLMs for Vulnerability Detection in Systems Software cites this paper.

Calibration Without Comprehension: Diagnosing the Limits of Fine-Tuning LLMs for Vulnerability Detection in Systems Software VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-07-04T04:29:35.045754Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T16:59:07.712294Z digest=sha256:b08f29b56e1803af907e629afc84a3e3c04b25b10d7d98072d5377f6fbf9aba1

Observation 1e111069-6050-4813-adcb-4620dcaf2905 · inbound

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection cites this paper.

Words Speak Louder Than Code: Investigating Cognitive Heuristics in LLM-Based Code Vulnerability Detection VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 41

Resolution
verified exact
arxiv_id, observed 2026-06-30T04:54:16.785146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T04:52:35.384665Z digest=sha256:1c3c12242dd198830c1bafebf94cfc929e87b0bd863c9dfa43402fbb2f431cbc

Observation 058933ad-70f3-41cf-a329-554b9b14ad00 · inbound

DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection cites this paper.

DREA: Decoupled Reasoning and Exploration Agents for Repository-Level Vulnerability Detection VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-02T05:13:52.726660Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:13:52.726660Z digest=sha256:5e53e362abf836b28f8562dc8e52c649a4016a2a3cb9f42b208ac05353069696

Observation 0049addd-b049-47cf-9033-f47aa6ea3e62 · inbound

VulnGym: Benchmarking Coding Agents for Repository-Level Vulnerability Detection cites this paper.

VulnGym: Benchmarking Coding Agents for Repository-Level Vulnerability Detection VulDetectBench: Evaluating the Deep Capability of Vulnerability Detection with Large Language Models

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-04T16:59:23.765035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T16:59:23.765035Z digest=sha256:675e137c36ba485ec4a687554ee0af47340266181d4348a49758f8be94cfd144