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It crossed my mind as well, are you aware of any benefits of RRF compared to cross-encoder (besides speed)? In RRF, there are manual hyper-parameters that the user will need to adjust, such as weights dedicated to sparse vs dense results.
@snexus I've found hardly any upside except computational efficiency. In staging setups, it gives us an additional degree of controllability (weighing) against various retrievers. But when using a non-embeddings based sparse retriever (BM25, tf-idf), I found RRF to be a better bet.
Hey @snexus
Are there any plans of including an option for [RRF](Reciprocal Rank Fusion) along with Marco and BGE for reranking?
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