What is BM25 and why is it still relevant?

BM25 is a classical sparse retrieval algorithm from the 1990s that ranks documents based on term frequency and inverse document frequency, with adjustments for document length. Despite being decades old, BM25 remains a strong baseline and is essential for matching exact terms. Modern RAG systems combine BM25 with dense embeddings rather than replacing it.