2026
Uncovering Pretraining Code in LLMs: A Syntax-Aware Attribution Approach
AAAI 2026technical
As large language models (LLMs) become increasingly capable, concerns over the unauthorized use of copyrighted and licensed content in their training data have grown, especially in the context of code. Open-source code, often protected by open source licenses (e.g, GPL), poses legal and ethical chal