The content discusses the importance of chunking documents effectively for Retrieval Augmented Generation (RAG) in the financial domain. It introduces a novel approach to chunk documents based on structural elements, highlighting the impact on information retrieval accuracy. The study focuses on U.S. Securities and Exchange Commission (SEC) Financial Reports, emphasizing the need for better pre-processing and chunking configurations. Various chunking methods are evaluated, including element-based approaches, showcasing improvements in retrieval and question-answering tasks. The results demonstrate the effectiveness of element-based chunking strategies in enhancing RAG performance.
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