Verified65% confidenceFactExact time
RRF is a tuning-free rank fusion algorithm that uses only rank positions, accumulating scores as 1/(k+rank), with the constant k typically set to 60.
3
Sources
65%
Confidence
Long-term
Relevance
10/15/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedReciprocal rank fusion (RRF) takes 1/(k + rank) for each document in each result list (k is usually 60), sums them, and reranks by total score; it relies only on ranks and requires no normalization.78% similarVerifiedRRF (Reciprocal Rank Fusion) weights and sums the results of two retrieval streams by the reciprocal of their ranks, requiring no score normalization, and is simple to implement with strong robustness.72% similarUnverifiedRRF uses only the rank in each list rather than the raw scores, so it is immune to differences in score scale between BM25 and vector similarity.66% similarUnverifiedNDCG@K takes into account both relevance strength and ranking position, assigning a relevance score to the document at each position and applying logarithmic discounting by ranking position, and finally dividing by the ideal ranking score for normalization so that the result falls between 0 and 1.64% similarUnverifiedElasticsearch uses k=60 as the default value of rank_constant in its RRF documentation.63% similar
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