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Paper Citation Record · LEDGER

To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2403.17218.

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

pith.paper-citation-record.v1
2403.17218 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 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 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T17:26:43.546948Z

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

17
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 5938a075-7b19-463c-99f6-176e1270e4a4 · inbound

Large Language Models for In-File Vulnerability Localization Can Be "Lost in the End" cites this paper.

Large Language Models for In-File Vulnerability Localization Can Be "Lost in the End" To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-08T17:26:43.546948Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T17:26:43.546948Z digest=sha256:297acefd46a536334c17c3713a40006636df09afcf9dc3897c7902c617b2f587

Observation dbc11be6-bc35-42c5-8b77-f5b5b45d917d · inbound

Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code cites this paper.

Case Study: Fine-tuning Small Language Models for Accurate and Private CWE Detection in Python Code To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-22T18:41:56.384859Z

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=pdf_text observed=2026-05-22T18:40:59.564031Z digest=sha256:f1f6556241baa077be95f8487f0275cc31650cb6ea983f0821f3d270fad160d4

Observation 84f05787-da1b-4643-b415-e4d5a805d04e · inbound

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection cites this paper.

What You Code Is What We Prove: Translating BLE App Logic into Formal Models with LLMs for Vulnerability Detection To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-04T19:25:52.524061Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T19:25:52.524061Z digest=sha256:d3d8d41cec7d0d5df5e90e074dd61cdd62a019ee4b0f8c56c2e66627cb794d14

Observation 12d81575-52df-4be9-891f-0042cbf506a7 · inbound

Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap cites this paper.

Do Fine-Tuned LLMs Understand Vulnerabilities? An Investigation into the Semantic Trap To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-22T11:41:30.146345Z

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=pdf_text observed=2026-05-22T11:38:16.149523Z digest=sha256:7dc1bcddb42cc2cb08e92a77fda3fd8633a7466cce6e48ce062a99c8cb02e5cc

Observation 6640d51c-9318-4700-8188-c86665e834f3 · inbound

Geometric quantification for nonlinear deformation in knitted fabrics cites this paper.

Geometric quantification for nonlinear deformation in knitted fabrics To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 53

Resolution
unresolved
no resolver link, observed 2026-07-15T11:27:58.396234Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-15T11:27:58.396234Z digest=sha256:6bf3851d81b1bb6a11f8de9c2f4b47581da10852f39afb7cffc773ae29c4607f

Observation c08f06ee-dfb2-463e-8c53-f71767cc489b · inbound

SAGE: Signal-Amplified Guided Embeddings for LLM-based Vulnerability Detection cites this paper.

SAGE: Signal-Amplified Guided Embeddings for LLM-based Vulnerability Detection To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 53

Resolution
metadata mismatch
arxiv_id, observed 2026-05-10T03:19:14.750477Z

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=pdf_text observed=2026-05-10T03:15:00.867443Z digest=sha256:e43b83a82d3176a370e0ace1165a96fcf0c65cb932f0488e9532c5ddc6fc8f63

Observation 81008e88-7402-467d-abb3-b10b9b5d31a1 · inbound

Veritas: Grounding LLM Agents for Reliable Vulnerability Reasoning over Stripped Binaries cites this paper.

Veritas: Grounding LLM Agents for Reliable Vulnerability Reasoning over Stripped Binaries To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 46

Resolution
verified exact
arxiv_id, observed 2026-05-15T14:05:54.705700Z

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=pdf_text observed=2026-05-15T14:04:16.443346Z digest=sha256:3cc02bac311ec92e95f6cfaaf19d2d42b4816f7bd196d9ec5e7a25591593e0d6

Observation 5e2853c0-3ef2-4558-bbb5-1092539093b9 · inbound

Veritas: Grounding LLM Agents for Reliable Vulnerability Reasoning over Stripped Binaries cites this paper.

Veritas: Grounding LLM Agents for Reliable Vulnerability Reasoning over Stripped Binaries To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 46

Resolution
unresolved
no resolver link, observed 2026-07-12T16:46:36.842198Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T16:46:36.842198Z digest=sha256:378cb77ce7da5332f434b68ec3f3fc32ce25ba3509dd6deb81cfbcba1e3de340

Observation 5f657626-cf83-4a56-bb59-34d36c2ee853 · inbound

Veritas: Grounding LLM Agents for Reliable Vulnerability Reasoning over Stripped Binaries cites this paper.

Veritas: Grounding LLM Agents for Reliable Vulnerability Reasoning over Stripped Binaries To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-02T14:03:38.331376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T14:03:38.331376Z digest=sha256:3113dbcef427db6158bb669e375438a627c3b90eed1484489dd65baf8dc36f01

Observation 119dc3e7-ae99-4ab2-b531-32a4998a71a5 · 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 To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 51

Resolution
verified exact
arxiv_id, observed 2026-05-20T09:18:10.088297Z

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=pdf_text observed=2026-05-20T09:16:56.388348Z digest=sha256:d4c5698b846e2e965a516c58f40b6b63bbfd5e3f41c031b03d5805c933ea0a04

Observation 6666b46c-95e7-4a9f-8936-d94b49258191 · inbound

SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks? cites this paper.

SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks? To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T17:33:45.233384Z

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=pdf_text observed=2026-06-29T17:29:36.006340Z digest=sha256:2ef02cb8713dd0948f15ea62f0f7ca6c451a7b1f4f42bb939f7134c5fec9ca92

Observation ca79777c-087b-4274-9059-94f8acdc096b · inbound

SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks? cites this paper.

SEC-bench Pro: Can Language Models Solve Long-Horizon Software Security Tasks? To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-02T13:10:40.467725Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T13:10:40.467725Z digest=sha256:aa0423f26dcfd9fd502426b8461aff7ebcf979c00444b04605ce91a08ff6bf60

Observation 6acdc03c-42ae-41e6-acf2-72ee1d1f00e8 · 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 To Err is Machine: Vulnerability Detection Challenges LLM Reasoning

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-02T05:13:53.197092Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T05:13:53.197092Z digest=sha256:1472592e814c83922a35f26b4345455c97cf5ef2c4e56028ab85a47551642faf