Asked about Retrieve broadly, then rank precisely
Why fuse search results by rank rather than score?
An answer that works
A BM25 score and a cosine similarity are on different scales with no meaningful conversion, so combining raw scores is arbitrary. Reciprocal rank fusion uses only position, which is comparable across any two ranked lists.
Then they push further
How does reciprocal rank fusion work?
Each document scores one divided by a constant plus its rank, summed over every list it appears in. A document ranked well by both searches wins. The constant, commonly 60, stops a single first place from dominating.
What gets marked up
Strong answers explain that keyword and vector scores are on different scales and cannot be compared directly, which is the whole reason to use ranks.
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