What is Reciprocal Rank Fusion (RRF) and how does it work?

Reciprocal Rank Fusion, or RRF, combines multiple ranked result lists into one by summing the reciprocal of each document's rank in each list, with a constant k usually set to 60. A document ranked first in both lists scores 1 over 61 plus 1 over 61. RRF requires no score calibration between retrievers, which makes it robust when combining systems with wildly different score distributions like BM25 and cosine similarity. It was introduced by Cormack and colleagues in 2009 and is the default fusion method in Elasticsearch, Weaviate, and Qdrant.