Rerankers are models that assign relevance scores to a query and retrieved documents. As the name suggests, they refine the ranking of documents initially retrieved using embedding-based methods …

In information retrieval (IR) and natural language processing (NLP), rerankers have emerged as critical components in refining search results. Rerankers offer a sophisticated solution to...

Apr 6, 2026 · Reranking is the second step in a RAG pipeline. First, your retriever fetches a set of candidate chunks. Then, a reranker evaluates the query and each candidate and reorders them …

Oct 20, 2025 · Rerankers take a query and retrieved documents and reorder them by relevance. They use cross-encoders to jointly encode query-document pairs, which is slower than vector search but …

Feb 26, 2026 · A reranker (cross-encoder) takes a query-document pair as a single input. The model attends to both texts jointly, catching relationships that independent encoding misses.

1 day ago · A Reranker is a model that takes a list of documents and reorders them, putting the most relevant ones at the top for a given question. In simple words, a Reranker is a smart sorter.

Aug 13, 2024 · Rerankers are specialized components in information retrieval systems that perform a crucial second-stage evaluation of search results. The need for more accurate and relevant search …