Hybrid Search: BM25 + Dense Vectors Explained (ANSWERED)
Medium RAG interview question on hybrid search: bm25 + dense vectors explained — architecture, trade-offs, eval, and production patterns.
TL;DR — Quick Answer
BM25 excels at exact keywords, SKUs, and rare tokens; dense vectors handle paraphrase and conceptual queries. Fuse rankings with RRF or calibrated weighted scores, retrieve a wide candidate set, rerank, then generate. Hybrid search is the default fix when vector-only RAG misses obvious keyword matches.
The Interview Question
Explain hybrid search: bm25 + dense vectors explained. How would you design, implement, and evaluate this in a production RAG system? Discuss trade-offs and failure modes.
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