BOUND refines LLMs' package-validity boundary via targeted editing to cut package hallucination rates by 79.9% on edit prompts and 65.4% on unseen prompts in recommendation tasks while generalizing to code generation.
Asleep at the keyboard? assessing the security of github copilot’s code con- tributions
3 Pith papers cite this work. Polarity classification is still indexing.
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In OSS repos that commit AI chat logs, AI use is heavier in smaller, less collaborative projects; chats almost always precede commits, quality signals do not broadly worsen, and developers trust their own AI code more than others'.
AI coding assistants introduce code issues that persist in 22.7% of cases across real projects, creating measurable long-term technical debt.
citing papers explorer
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Mitigating Package Hallucinations in Large Language Models via Model Editing
BOUND refines LLMs' package-validity boundary via targeted editing to cut package hallucination rates by 79.9% on edit prompts and 65.4% on unseen prompts in recommendation tasks while generalizing to code generation.
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From Conversation to Contribution: Characterizing Coding Agent in Open-Source Software
In OSS repos that commit AI chat logs, AI use is heavier in smaller, less collaborative projects; chats almost always precede commits, quality signals do not broadly worsen, and developers trust their own AI code more than others'.
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Debt Behind the AI Boom: A Large-Scale Empirical Study of AI-Generated Code in the Wild
AI coding assistants introduce code issues that persist in 22.7% of cases across real projects, creating measurable long-term technical debt.