Reranking

November 9, 2022 Charlie Hull

Re-ordering of results using a secondary post-process applied to a previously generated candidate set. Reranking algorithms can be more computationally expensive as they’re applied, typically, to smaller subsets of the corpus. An example might be applying cosine similarity scoring between doc and query embeddings (vectors) – too expensive to apply to all potential results in large corpi.