Vectorless Retrieval-Augmented Generation: A BM25-Based Alternative to Embedding-Driven RAG Systems
Retrieval Augmented Generation (RAG) augments large language models using external knowledge at the inference stage to increase factual accuracy and reduce hallucinations. Most existing RAG models employ dense vectors for information retrieval, which facilitates semantic matching at the expense of increased computation...