Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:56:18.596190Z
Paper Citation Record · LEDGER
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.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-06T21:56:18.596190Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-01T12:35:40.705180Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T05:16:39.187629Z
71 of 71 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 8ff9d342-76c2-4b61-bf7a-2f06568368ad · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation GPT-4 Technical Report
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Observation 1a155d9c-1b94-4ffd-b786-700d402695a2 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 56b9bdbe-4108-4d1e-8b43-b578b3301c52 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 4
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Observation 8e14e363-ecd0-4f9a-b114-9e2faf840d95 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Program Synthesis with Large Language Models
Reference 5
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Observation e2de48fb-7217-4f70-912c-772645ae31bc · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 41ed9028-797f-462b-a408-5b5ccc48c38c · outbound
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
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Observation 381c30dd-e45d-4868-af24-85cbb8ecd9f9 · outbound
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
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Observation 7c077dd7-5641-476a-beaf-151be54d99cc · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 9
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Observation 95497402-8d8d-4dde-993a-b885f5fc314f · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Díaz Ferreyra
Reference 10
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Unavailable: canonical work link unavailable.
Observation 93b7a2c7-a617-4620-a95d-74c16efddfe5 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Evaluating Large Language Models Trained on Code
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Observation ef622403-68dc-4788-8970-3b8212141c85 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 12
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Observation 099ab0db-451b-4590-8ab1-0a5f28bb2120 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 3c93150b-bb1e-4124-ac59-55d00c117570 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 14
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Observation 6cc2d0c1-b3e9-4116-852c-88522e4d44a3 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation The Llama 3 Herd of Models
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Observation f4fe08aa-b299-47f2-a5bd-b775423e46be · outbound
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
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Observation f2c3cb7b-2529-41c1-a67d-7d3d0751ad94 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 17
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Observation 944f1d4f-09ea-4b67-aed3-b24b26a03386 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 18
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Observation 5d5e3793-da38-420a-b369-0ca315d1327d · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 19
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Observation 6f09ea14-5347-4bff-8c04-402194e7dde7 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 664becac-4e6d-4ffa-ae56-b824f9693ae7 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 21
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Observation 7abfceaf-1df1-4871-bd14-2a1176458cd0 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 22
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Observation e06a1d3e-5c2a-4c84-b795-77004919e5de · outbound
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
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Observation cda5eb20-ed5a-43ba-a5cb-544a197eaae5 · outbound
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
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Observation 444ffeff-770e-4774-9a20-57f415a26e2b · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation a72346db-7b5d-4369-8d46-9fb2cb1d890f · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation a4bf3396-faee-4a4c-92bb-0ba74e80e4a9 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 27
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Observation a17341fa-f138-438f-ab1b-ac5536098172 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation cf2c0ff5-d147-4f38-9318-ace95b7c5197 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 29
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Observation fbc1990e-4732-4917-9651-91e14b028042 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 30
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Observation 7aa096ee-fc0b-4f57-952c-28da3934620d · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 31
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Observation 2a11933e-3214-4c08-8645-3bf91e602ba2 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation InDeep Learning for Code Workshop
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Observation 91ed04cf-ce39-45cd-9599-a041f5065bdd · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 33
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Observation f77fe6ce-1a89-4766-b02c-6bbb882a3ec5 · outbound
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
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Observation 69978a07-0878-4b0f-8835-fc13aace2e3c · outbound
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
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Observation 2027c3a7-483a-4a08-ae6f-717bde152e03 · outbound
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
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Observation 7f40feb8-2d47-4504-a545-bc07b6e3ec97 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation b09a5185-f90e-478d-b85e-9429dfd6169c · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation c02cb703-b8c7-4e2b-8749-e499767290f0 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 8cd3183e-d3f1-4098-80ce-906a89d75de1 · outbound
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
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Observation 03db4cd7-c00c-4d29-88b1-d827ad4d3cb2 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation ccd0133c-eae8-466b-94cb-8a7b26605aff · outbound
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Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 55037949-d80b-4586-913f-7daeff7f655f · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 514fd207-0a8a-41f9-95ec-da0704fcbfcb · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Code Llama: Open Foundation Models for Code
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Observation beedbbc5-61c8-43bd-82da-f475037927be · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 184b181e-cc8d-48d9-8537-467707e51075 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 7406ffa1-a664-4fa0-b22b-7501a5c456de · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 48
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Observation 8fb2a24a-fda0-448d-bdfd-91664e3c824e · outbound
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
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Observation 76321b80-7bce-4802-ad99-becd12186589 · outbound
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
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Observation b714b66b-5d2a-4afe-8544-81769c0bcdd2 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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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
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Observation a5036068-b99c-411d-9814-76a1b5b4af63 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 35ff4bb3-8ba4-4fbb-9272-ca256ea64992 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 54
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Observation 45e4f795-f3ee-4a94-a3ed-95e2960e5a93 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 55
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Observation 1ecb443c-5029-4e9a-bdee-72adbfe6edb9 · outbound
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Observation 624df213-6cb0-401a-9eed-3537e9ecf324 · outbound
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Observation 2c725ddf-2f77-46cf-8740-b74455af6572 · outbound
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
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Observation aa65cdf4-81dd-412c-a2df-fd8c8111292e · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation f3b7bbdf-ea20-44d7-a450-3dfe71d2ccaf · outbound
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Observation 6c134596-85af-4326-b859-fde9392fb613 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
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Observation 2f1fc241-f75d-4886-8f69-75cd06554bcf · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 62
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Observation 75cb6687-9024-4446-8f2a-5bcc712d1fa4 · outbound
Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation Unresolved cited work
Reference 63
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Observation 795ba5d7-affc-4926-b78f-418605059aa0 · outbound
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
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Observation 1b6d783d-74d7-43c9-ba65-c1dc4a45a440 · outbound
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
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Observation c986d335-aadc-4240-937c-b805adc62de5 · outbound
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Observation 1b1fca54-0b41-476e-8e38-070b9fd8f551 · outbound
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Observation f72ee0ec-5d7d-4f1b-8715-5f416f733090 · outbound
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
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Observation fb16ac20-32e9-4b06-a05e-8bda01f7213e · outbound
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
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Observation ed6f5078-9715-4c54-9afb-d4f809813165 · outbound
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
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Observation 1fc9b21b-977d-4246-9e3a-bef37b96a1fd · outbound
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
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Observation 72b81d3f-176f-496b-b363-a38a3e693a92 · inbound
Why Do Large Language Models Generate Harmful Content? Guiding AI to Fix Its Own Flaws: An Empirical Study on LLM-Driven Secure Code Generation
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Observation 18507cca-571b-4900-820c-5b8417fa5087 · inbound
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
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Observation 092d2282-36b0-466c-8b23-140bc9bad482 · inbound
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Observation 22c523a7-62ea-49e1-af1e-7fd883e23c4a · inbound
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Reference 83
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Observation 5f6fb6a1-82d7-4672-b651-19bbef594d74 · inbound
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
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