Data Recipe

"Data recipes" in the context of large language models (LLMs) refer to optimized combinations of training data sources designed to improve model performance on specific tasks or across a range of benchmarks. Current research focuses on developing algorithms and frameworks to automatically generate and evaluate these recipes, including methods for programmatically creating synthetic data and efficiently processing massive, heterogeneous datasets. This work is significant because it addresses the high cost and complexity of manually curating LLM training data, potentially leading to more efficient and effective LLM development and deployment across various applications.