Hybrid Search and Reciprocal Rank Fusion
Hybrid search combines lexical and vector results. Since their raw scores may use different scales, rank fusion such as Reciprocal Rank Fusion (RRF) can merge result lists using rank positions. A practical pipeline applies the same access filters, merges and deduplicates candidates, optionally reranks them, and selects a bounded context.
Hybrid retrieval is not always best; compare it against lexical-only and vector-only baselines on your corpus.
Diagram
Implementation example
Question -> lexical search ----\
-> RRF merge -> deduplicate -> rerank
Question -> vector search -----/💡 Rank fusion avoids blindly adding incomparable raw scores.
Key Takeaways
- Inspect the relevant pipeline stage instead of guessing.
- Preserve source provenance, versions, and access scope.
- Measure quality on representative queries.
Knowledge Check
Why use RRF?