Digger: Detecting Copyright Content Mis-usage in Large Language Model Training. (arXiv:2401.00676v1 [cs.CR])

Pre-training, which utilizes extensive and varied datasets, is a critical
factor in the success of Large Language Models (LLMs) across numerous
applications. However, the detailed makeup of these datasets is often not
disclosed, leading to concerns about data security and potential misuse. This
is particularly relevant when copyrighted material, still under legal
protection, is used inappropriately, either intentionally or unintentionally,
infringing on the rights of the authors.

In this paper, we introduce a detailed framework designed to detect and
assess …

applications copyright critical data data security datasets factor language language models large large language model llms model training relevant security training