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Paper Citation Record · LEDGER

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation

As of 8 August 2026, this Paper Citation Record lists 71 of 71 outbound references and 6 inbound Pith citation observations for arXiv:2506.23034.

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

pith.paper-citation-record.v1
2506.23034 v1

Coverage vector

measured 71 of 71 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:56:18.596190Z

measured 77 of 77 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-01T12:35:40.705180Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T05:16:39.187629Z

Reference resolution

71 of 71 outbound references displayed

  • verified exact1
  • verified fuzzy3
  • unresolved66
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8ff9d342-76c2-4b61-bf7a-2f06568368ad · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 1

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:23.451183Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:12.811416Z digest=sha256:1c48dec4e36845f1e6801c3278c47f5a70bed9ca2a35f2f51eaf5ad0a965015b

Observation 3044b31d-b146-4672-b88f-a9661246015a · outbound

This paper cites GPT-4 Technical Report.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation GPT-4 Technical Report

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:12.903896Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:12.903896Z digest=sha256:24c4d0a3a806d532ed94c091cd42ca9c4f5e169f6892982fce85b404cefa9be0

Observation 1a155d9c-1b94-4ffd-b786-700d402695a2 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 3

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:23.240361Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:13.011732Z digest=sha256:29b25a99be0fcf454c81d44d0ad77b9687e20a35b7d979695ff527dbb3f4f893

Observation 56b9bdbe-4108-4d1e-8b43-b578b3301c52 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:13.120528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:13.120528Z digest=sha256:a7e9cce761eac2f65040e16ae4a52084c66d0646ba60d5a6f9bf76fbfc023ba4

Observation 8e14e363-ecd0-4f9a-b114-9e2faf840d95 · outbound

This paper cites Program Synthesis with Large Language Models.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Program Synthesis with Large Language Models

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:13.211404Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:13.211404Z digest=sha256:6004c65552eef883e087aeb2b26b14ab39cb47c7b70911e806f4758deeb99ad4

Observation e2de48fb-7217-4f70-912c-772645ae31bc · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 6

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:22.970387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:13.312827Z digest=sha256:a5e703640c49ed56b954cdde9a5e0701030b7b506e9b260576abe3ccdf59fa3a

Observation 41ed9028-797f-462b-a408-5b5ccc48c38c · outbound

This paper cites CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation CyberSecEval 2: A Wide-Ranging Cybersecurity Evaluation Suite for Large Language Models

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:13.412290Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:13.412290Z digest=sha256:f7efbbf07ea9c849bc67efa0fb4cfa3d735025c672382cd476892606281035f1

Observation 381c30dd-e45d-4868-af24-85cbb8ecd9f9 · outbound

This paper cites Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Purple Llama CyberSecEval: A Secure Coding Benchmark for Language Models

Reference 8

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:13.509418Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:13.509418Z digest=sha256:be874453c371af44e1d3c9abed95b1440215b57cb9e2889d449e8e964399a286

Observation 7c077dd7-5641-476a-beaf-151be54d99cc · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:13.648579Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:13.648579Z digest=sha256:9ae794463cfa87e9ea35f0cd8841a0bc88ca906018627732a4a17d1f94bea9a0

Observation 95497402-8d8d-4dde-993a-b885f5fc314f · outbound

This paper cites Díaz Ferreyra.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Díaz Ferreyra

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:13.790703Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:13.790703Z digest=sha256:0eab63c56cd252ba7aa19fb6c7fb4f3b4e50c8745b6d57b1cca3abd75786b183

Observation 93b7a2c7-a617-4620-a95d-74c16efddfe5 · outbound

This paper cites Evaluating Large Language Models Trained on Code.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Evaluating Large Language Models Trained on Code

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:13.913928Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:13.913928Z digest=sha256:b137ff9fd9d7368cde5ab3cc8d66d40d2499051835e7597ad3736e4ba7dff069

Observation ef622403-68dc-4788-8970-3b8212141c85 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 12

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:22.835364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:14.013377Z digest=sha256:11d3610189f6fb3e416b9bc7185cdd12caa2026be7e035e2c7120f0444774be0

Observation 099ab0db-451b-4590-8ab1-0a5f28bb2120 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 13

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:22.630416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:14.159029Z digest=sha256:cd7e3bc9bc3918323d2428ab3866c4ab64bebbdd4f0a2179387b0d2c42be6a13

Observation 3c93150b-bb1e-4124-ac59-55d00c117570 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:14.281597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:14.281597Z digest=sha256:3c188344b7903002ac1ff80360ffc0fe96ef09cfafc827e6a6b78bb22ede49c5

Observation 6cc2d0c1-b3e9-4116-852c-88522e4d44a3 · outbound

This paper cites The Llama 3 Herd of Models.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation The Llama 3 Herd of Models

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:14.378528Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:14.378528Z digest=sha256:1d97d86b87c2548b44f22d1df0f232231c90f1711af062cc6ee42e06b443a811

Observation f4fe08aa-b299-47f2-a5bd-b775423e46be · outbound

This paper cites InCoder: A Generative Model for Code Infilling and Synthesis.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation InCoder: A Generative Model for Code Infilling and Synthesis

Reference 16

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:14.502560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:14.502560Z digest=sha256:c3a9af5e18d8283783caa505023aecf36344275d635f369dcbb7517d97e52941

Observation f2c3cb7b-2529-41c1-a67d-7d3d0751ad94 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:14.637311Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:14.637311Z digest=sha256:893d561ca55119e93a1ee6fa2e48c39fb7bb722c274fe8aaaa975fbd7b693354

Observation 944f1d4f-09ea-4b67-aed3-b24b26a03386 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 18

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:14.812643Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:14.812643Z digest=sha256:9fc6ed4c287368afac0f67daf0a48d26662459917ce74d01f22e01275180da61

Observation 5d5e3793-da38-420a-b369-0ca315d1327d · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 19

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:22.443362Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:14.947916Z digest=sha256:341f6994359a594185aaa57fd4b6a641d3b8e6a0f983b4aa44419b45858c77ed

Observation 6f09ea14-5347-4bff-8c04-402194e7dde7 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 20

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:22.225241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:15.026984Z digest=sha256:4f91de4cf2378d1c92cb6cb4259849a1cfcd12cb3e9133c2394610204c94d23c

Observation 664becac-4e6d-4ffa-ae56-b824f9693ae7 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 21

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:22.068759Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:15.113794Z digest=sha256:7b63a81247a602529dab980ee267179d0813a13917977b98a1b21af865b8bf3c

Observation 7abfceaf-1df1-4871-bd14-2a1176458cd0 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 22

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.177714Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.177714Z digest=sha256:837a92da2e1655b64564017ac60337801e4b71a65588df7aefc5d866e9e1e0c5

Observation e06a1d3e-5c2a-4c84-b795-77004919e5de · outbound

This paper cites AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation AgentCoder: Multi-Agent-based Code Generation with Iterative Testing and Optimisation

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.236015Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.236015Z digest=sha256:90d7375376c57fe8caf65fe1d97bebafe280ee7c40d518df2ffab2229a28a423

Observation cda5eb20-ed5a-43ba-a5cb-544a197eaae5 · outbound

This paper cites CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation CODESIM: Multi-Agent Code Generation and Problem Solving through Simulation-Driven Planning and Debugging

Reference 24

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.284469Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.284469Z digest=sha256:bab36a62d306b72c30cbc31159beb247a515946fcd90d41e1feacf6ac4e031e7

Observation 444ffeff-770e-4774-9a20-57f415a26e2b · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 25

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:21.906357Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:15.333736Z digest=sha256:1187a68a8de7783f2cc616c60f83fba779857cb75bf470a2ebbcd92485dac26c

Observation a72346db-7b5d-4369-8d46-9fb2cb1d890f · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 26

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:21.732074Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:15.445057Z digest=sha256:de8be9b63da178543841e6e6d584aa6db9111f64c8550ff215efab85be210a1e

Observation a4bf3396-faee-4a4c-92bb-0ba74e80e4a9 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.571084Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.571084Z digest=sha256:99ec6e624110690a939fe6a133e22042f66f72ba624b78a290f3e1e5cc4212ec

Observation a17341fa-f138-438f-ab1b-ac5536098172 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 28

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.643667Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.643667Z digest=sha256:e1219315ccc3020c87fc9dc8e23237e12013c75f8f8d8d3f2cbe6ae3cd52ace9

Observation cf2c0ff5-d147-4f38-9318-ace95b7c5197 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 29

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.813003Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.813003Z digest=sha256:264c0c2620a8284e2dbb7da7128d0b10a04b60203a52a8e184d056077ea73e16

Observation fbc1990e-4732-4917-9651-91e14b028042 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 30

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:21.251473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:15.889856Z digest=sha256:6c20363292db94abae4c0314a09f0be75e23667ae7104680cc2f812a07c140ce

Observation 7aa096ee-fc0b-4f57-952c-28da3934620d · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 31

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.960455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.960455Z digest=sha256:e9eb90985be6a7fb4b8b7b5951a1f9617928a2db8a98fd896e616861a086811a

Observation 2a11933e-3214-4c08-8645-3bf91e602ba2 · outbound

This paper cites InDeep Learning for Code Workshop.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation InDeep Learning for Code Workshop

Reference 32

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:56:21.451927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:15.679175Z digest=sha256:6387af264d43b0a64e29560d6667927a6ec0c8a7979b31c1eed73f569c461952

Observation 91ed04cf-ce39-45cd-9599-a041f5065bdd · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.088997Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.088997Z digest=sha256:5bb03fd0ba88fc7ca7ce0b6d914cce847960601a2e5304213d3924043688ecb1

Observation f77fe6ce-1a89-4766-b02c-6bbb882a3ec5 · outbound

This paper cites Chain-of-Thought Prompting of Large Language Models for Discovering and Fixing Software Vulnerabilities.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Chain-of-Thought Prompting of Large Language Models for Discovering and Fixing Software Vulnerabilities

Reference 34

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.187532Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.187532Z digest=sha256:381f54567b344f7b02a060cda941b52ff5c6440b233bb73f8dcf1956d7d56d41

Observation 69978a07-0878-4b0f-8835-fc13aace2e3c · outbound

This paper cites APPATCH: Automated Adaptive Prompting Large Language Models for Real-World Software Vulnerability Patching.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation APPATCH: Automated Adaptive Prompting Large Language Models for Real-World Software Vulnerability Patching

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.258162Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.258162Z digest=sha256:00ddaaa5567452f87520b0919dae49f0c32ef7d72dbd1069c9539d71338da354

Observation 2027c3a7-483a-4a08-ae6f-717bde152e03 · outbound

This paper cites StarCoder 2 and The Stack v2: The Next Generation.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation StarCoder 2 and The Stack v2: The Next Generation

Reference 36

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.031848Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.031848Z digest=sha256:7d20a5adde4f7c5e778999b13e8fbff02e1c75b2d8b691053973fe1071fbbc48

Observation 7f40feb8-2d47-4504-a545-bc07b6e3ec97 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 37

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:20.787227Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:16.402406Z digest=sha256:786984c37ef6736ff770be96d52191058f94bcae88b525c1e3f12636dab3f364

Observation b09a5185-f90e-478d-b85e-9429dfd6169c · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 38

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.129163Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.129163Z digest=sha256:22920d58dcde7a042fb25da8ad62536879f142ec9d4f713f6b6499d7315703e3

Observation c02cb703-b8c7-4e2b-8749-e499767290f0 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 39

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.520645Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.520645Z digest=sha256:0a1915bf77d2f2b6ebdf5843e01bd7559fe592e2456c5ac07d1124b951ef54e5

Observation 8cd3183e-d3f1-4098-80ce-906a89d75de1 · outbound

This paper cites On the Security Vulnerabilities of Text-to-SQL Models.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation On the Security Vulnerabilities of Text-to-SQL Models

Reference 40

Resolution
verified exact
local_arxiv, observed 2026-08-06T21:56:19.085075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:16.581011Z digest=sha256:033fa85754fdb6667c0a2238c82e9f40e1d8d0783e7e7f422294d6a021c55b77

Observation 03db4cd7-c00c-4d29-88b1-d827ad4d3cb2 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 41

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:21.035791Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:16.337306Z digest=sha256:9c7a4a6721237bdb932670e9fb5b4e5f74fc654698068e10e0ff39f749a610e4

Observation ccd0133c-eae8-466b-94cb-8a7b26605aff · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 42

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:20.601809Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:16.770367Z digest=sha256:8bb933bed597020d0af74815bbe0d28420dc6ab63d48aff86c7b41258292d68a

Observation 0ce9d3a7-7e4a-4a1a-933f-e6a09e47aa59 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.464148Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.464148Z digest=sha256:ee8ec399cba455de2e12a130dc506356f40959fee1710330e236b6bd922c24db

Observation 55037949-d80b-4586-913f-7daeff7f655f · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 44

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:20.403489Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:16.907125Z digest=sha256:41152eeaa655cc7262d5bdf13fc89ed1de3448248655b59c331691c409e6b33e

Observation 514fd207-0a8a-41f9-95ec-da0704fcbfcb · outbound

This paper cites Code Llama: Open Foundation Models for Code.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Code Llama: Open Foundation Models for Code

Reference 45

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.990213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.990213Z digest=sha256:ecac79553d395e466884945d4d68d64bad02d50129af5b214b7a5e6aad604306

Observation beedbbc5-61c8-43bd-82da-f475037927be · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.666941Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.666941Z digest=sha256:664aae3f430de795bb4a18b10663c65f9c920499d88f2f2c2d9de51ba472aac6

Observation 184b181e-cc8d-48d9-8537-467707e51075 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 47

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.122797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.122797Z digest=sha256:2cdd59d08753164dfcb70bbacddba1d1eaecbcf14ff78cbbe601673e9aa22d89

Observation 7406ffa1-a664-4fa0-b22b-7501a5c456de · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:16.839075Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:16.839075Z digest=sha256:b63acfba0d26cee68c9eaac856acbb35f457d0c79ce23e108bbb5f3d8044da6a

Observation 8fb2a24a-fda0-448d-bdfd-91664e3c824e · outbound

This paper cites RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation RepairLLaMA: Efficient Representations and Fine-Tuned Adapters for Program Repair

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.257242Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.257242Z digest=sha256:38cdf15769bf39d24085d0c987a476dcd1abaeeb365144fead1aa4d060b0833c

Observation 76321b80-7bce-4802-ad99-becd12186589 · outbound

This paper cites Prompting Techniques for Secure Code Generation: A Systematic Investigation.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Prompting Techniques for Secure Code Generation: A Systematic Investigation

Reference 50

Resolution
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no resolver link, observed 2026-08-06T21:56:17.328324Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.328324Z digest=sha256:7d9e44b5ea3038302c8e52fcff9e584aa1dbd136c862a5f773dab650c30b9762

Observation b714b66b-5d2a-4afe-8544-81769c0bcdd2 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 51

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:20.145297Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:17.045317Z digest=sha256:22b2a025946147aaee91defac16c9f663cb50625421c1e5cbc956825e7d68177

Observation 4fbbde43-0fb6-43bd-9fe6-e4c9150e227f · outbound

This paper cites CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation CYBERSECEVAL 3: Advancing the Evaluation of Cybersecurity Risks and Capabilities in Large Language Models

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.452505Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.452505Z digest=sha256:dcd683bad9877921e0d455458961b57cb8bd5e723605192e74e9f67825b19656

Observation a5036068-b99c-411d-9814-76a1b5b4af63 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 53

Resolution
metadata mismatch
raw_fallback, observed 2026-08-06T21:56:18.955881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:17.189053Z digest=sha256:5bd9dc87c3259dc12c49bc6d4296ef7497c7322f1c11e2d73628a5d82bf26b97

Observation 35ff4bb3-8ba4-4fbb-9272-ca256ea64992 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 54

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:19.853468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:17.656981Z digest=sha256:dd562d50a75512e0c4df7b89f454d28302fec36d5672ffc1c0210feaaf89d384

Observation 45e4f795-f3ee-4a94-a3ed-95e2960e5a93 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 55

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.722076Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.722076Z digest=sha256:1110572918d94ec3b0eb676fefdeaa093654604e2c6dbf89f73d9fc4f49f6581

Observation 1ecb443c-5029-4e9a-bdee-72adbfe6edb9 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 56

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:20.007256Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:17.387529Z digest=sha256:6f1bccddfef0bf38096df2ba23721708386ef0571301cf7ec3f975e0d765cfbd

Observation 624df213-6cb0-401a-9eed-3537e9ecf324 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 57

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.873880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.873880Z digest=sha256:e13042cdd5bdf5a886b8cafc4e83726335215c6c861af746d9347a31129ca7cb

Observation 2c725ddf-2f77-46cf-8740-b74455af6572 · outbound

This paper cites Is Your AI-Generated Code Really Safe? Evaluating Large Language Models on Secure Code Generation with CodeSecEval.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Is Your AI-Generated Code Really Safe? Evaluating Large Language Models on Secure Code Generation with CodeSecEval

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.536958Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.536958Z digest=sha256:d4642f029678b0cd2a7d5cee77b304f279d8a6ed6944dc9fbbe9052b3542be68

Observation aa65cdf4-81dd-412c-a2df-fd8c8111292e · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 59

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:19.730435Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:18.058616Z digest=sha256:e8b61dc17780fcfb8643a5eb6acb16150ff1b3cffc947784749d227e76dc4668

Observation f3b7bbdf-ea20-44d7-a450-3dfe71d2ccaf · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 60

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:18.198206Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:18.198206Z digest=sha256:0f7b9bb864f0cad89c3bc7fa12a7e65a825f7b541505b82427ca6f7485d77dad

Observation 6c134596-85af-4326-b859-fde9392fb613 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 61

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.783229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.783229Z digest=sha256:9acd97553949805d2dc23e30bd7c5dc60855b729904bd89c6dd8cc20d183fb9d

Observation 2f1fc241-f75d-4886-8f69-75cd06554bcf · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:18.443498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:18.443498Z digest=sha256:1b35ba0a6ede8fed66a5d1a2dad6a9852a2434b0da1ffbbb7a9917033578fd58

Observation 75cb6687-9024-4446-8f2a-5bcc712d1fa4 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:17.972864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:17.972864Z digest=sha256:7838181c4d772a1d62e0654640c0d6a3664ea9c34020270bc23fbfb053052d43

Observation 795ba5d7-affc-4926-b78f-418605059aa0 · outbound

This paper cites DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation DeepSeek-Coder-V2: Breaking the Barrier of Closed-Source Models in Code Intelligence

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:18.596190Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:18.596190Z digest=sha256:c59091ab64d23e2e0f70932009bd9d079863214052abdde97e715a3bff3d214a

Observation 1b6d783d-74d7-43c9-ba65-c1dc4a45a440 · outbound

This paper cites InProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation InProceedings of the 33rd ACM SIGSOFT International Symposium on Software Testing and Analysis

Reference 67

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:18.295010Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:18.295010Z digest=sha256:bf68220c93fe100c01a640f850fd5e7f984a0ee24137b984f93554b8bc3f1f38

Observation c986d335-aadc-4240-937c-b805adc62de5 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 68

Resolution
unresolved
raw_fallback, observed 2026-08-06T21:56:19.407675Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:18.383973Z digest=sha256:7ad9fe2f6a3a4c74764faf1f90138599538040a42538220ef83a5f38a8a24dde

Observation 1b1fca54-0b41-476e-8e38-070b9fd8f551 · outbound

This paper cites an unresolved cited work.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work

Reference 70

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:18.532510Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:18.532510Z digest=sha256:f2f6b98dffb78c4a7189d35ffd38ab0376bafd500c9de2e651bba51d769b19bc

Observation f72ee0ec-5d7d-4f1b-8715-5f416f733090 · outbound

This paper cites InPro- ceedings of the 30th ACM joint european software engineering conference and symposium on the foundations of software engineering.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation InPro- ceedings of the 30th ACM joint european software engineering conference and symposium on the foundations of software engineering

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:14.731543Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:14.731543Z digest=sha256:e6f4e5960e24bd840668d42b6292bb77a7d34297adeeb7936466e431c9dde187

Observation fb16ac20-32e9-4b06-a05e-8bda01f7213e · outbound

This paper cites In2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation In2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC)

Reference 2023

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:56:21.585440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:15.499676Z digest=sha256:c3e38ae1f77c5bedf501a51d9229de3eec3b6b2e56ddc8cbf9359dad20d0006a

Observation ed6f5078-9715-4c54-9afb-d4f809813165 · outbound

This paper cites Code Security Vulnerability Repair Using Reinforcement Learning with Large Language Models.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Code Security Vulnerability Repair Using Reinforcement Learning with Large Language Models

Reference 2024

Resolution
unresolved
no resolver link, observed 2026-08-06T21:56:15.385870Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T21:56:15.385870Z digest=sha256:f11b413e809bd41b2d12ae56f111e076699aa81ddc1b111f159be04a1d89a989

Observation 1fc9b21b-977d-4246-9e3a-bef37b96a1fd · outbound

This paper cites InThe Thirteenth International Conference on Learning Representations.

Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation InThe Thirteenth International Conference on Learning Representations

Reference 2025

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T21:56:19.542965Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T21:56:18.131163Z digest=sha256:944d1d011d2e10ba689eb91980dbdfa876374145741f31f6d4df8555fdfc3b9d

Pith citing papers

Observation 72b81d3f-176f-496b-b363-a38a3e693a92 · inbound

Why Do Large Language Models Generate Harmful Content? cites this paper.

Why Do Large Language Models Generate Harmful Content? Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-11T10:21:04.527017Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-10T15:31:13.545599Z digest=sha256:789b40cfc887ffbda77b540fdc74eab20ffd41dab9e1998b8a988e0662fd8c28

Observation 18507cca-571b-4900-820c-5b8417fa5087 · inbound

On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies cites this paper.

On Fixing Insecure AI-Generated Code through Model Fine-Tuning and Prompting Strategies Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-11T20:26:09.999076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-08T09:12:15.486780Z digest=sha256:4447cac7cbb83af4d8b70a5dfa79023fdd33fbfaf1121c4d906217531bb82afe

Observation 092d2282-36b0-466c-8b23-140bc9bad482 · inbound

Quality and Security Signals in AI-Generated Python Refactoring Pull Requests cites this paper.

Quality and Security Signals in AI-Generated Python Refactoring Pull Requests Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation

Reference 34

Resolution
verified exact
arxiv_id, observed 2026-05-21T03:03:55.913832Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-21T03:01:29.056336Z digest=sha256:3faa010e46c86bf15e9f7d86a327d5bae49426df47aa661c8f05409475b39762

Observation 22c523a7-62ea-49e1-af1e-7fd883e23c4a · inbound

Security of LLM-generated Code: A Comparative Analysis cites this paper.

Security of LLM-generated Code: A Comparative Analysis Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation

Reference 83

Resolution
verified exact
arxiv_id, observed 2026-05-25T05:16:39.190244Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-05-25T05:16:26.372764Z digest=sha256:5bdf5bbd7d9b20d4711bb647964559601db8ec214b032e5102be4c069e0597e3

Observation 1caeef22-fbb2-43a9-8398-072920ef6da8 · inbound

From Evaluation to Optimisation: Hierarchy-Aware Training Signals for CWE Prediction in Python cites this paper.

From Evaluation to Optimisation: Hierarchy-Aware Training Signals for CWE Prediction in Python Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation

Reference 33

Resolution
unresolved
no resolver link, observed 2026-08-01T08:38:07.841873Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-01T08:38:07.841873Z digest=sha256:d6f66637cb4f3de4980c86e2c97c4b9b265471e7f78025f747925f41bdc90231

Observation 5f6fb6a1-82d7-4672-b651-19bbef594d74 · inbound

Tool-Guided Retrieval-Augmented Repair for Securing LLM-Generated C Code cites this paper.

Tool-Guided Retrieval-Augmented Repair for Securing LLM-Generated C Code Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation

Reference 104

Resolution
unresolved
no resolver link, observed 2026-08-01T12:35:40.705180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T12:35:40.705180Z digest=sha256:832be37d1e3efd66ae0999c85639d8ee8c3106476634268bc90e25b6ea226f62