Optimizing Retrieval-Augmented Generation Systems: Evaluating Document Splitting Methods and Retrieval Techniques Across Diverse Content Types

Effective retrieval strategies are crucial for Retrieval-Augmented Generation (RAG) systems to provide accurate and relevant responses. This study evaluates the performance of different document splitting methods and retrieval techniques across diverse document types, including textbooks, articles, and novels, to identify optimal approaches for enhancing retrieval accuracy and efficiency.