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  5. Reciprocal Rank Fusion
Retrieval & Searchaka RRF

Reciprocal Rank Fusion

A method for combining ranked results from multiple retrieval systems by scoring each result based on its rank position, simple and effective for hybrid search.

Ask Melo about this← all terms

Reciprocal Rank Fusion (RRF) merges ranked lists from different retrieval systems — such as BM25 and dense retrieval — by assigning each result a score of 1/(k + rank) and summing across lists. The constant k (typically 60) dampens the influence of top ranks. RRF requires no training, no score normalization, and consistently outperforms individual rankers, making it the default fusion method in most hybrid search implementations.

Related terms

Hybrid SearchRerankingBM25Dense RetrievalCosine SimilarityIndexing

Where Reciprocal Rank Fusion comes up

  • Garry Tan Ships GBrain Evals — But Who Grades the Grader?
  • Castform + Neon: A 4B Open Model Matches GPT-5.6 Sol at 1/100th the Cost
  • Semantic vs vector vs hybrid search: the most confusable topic on the AI-103 exam
  • How Gary Tan Shipped 400x More Code Using Claude Code & AI Agents