medium10 pts · first answer countsragreranking

Adding a reranker

In a RAG pipeline, you retrieve 50 candidate chunks with vector search and then run a cross-encoder reranker to keep the top 5. Why?

A.The reranker creates new documents that are not in the indexB.The reranker reduces the size of the vector indexC.A cross-encoder reads query and chunk together, giving more accurate relevance scores than embedding similarity, but it is too slow to run on the whole corpusD.The reranker translates documents into the user language

← Embeddings miss exact product codes Who runs the tool →