---
title: "Reranking"
type: "glossary term"
url: "https://aifordevs.org/glossary#reranking"
markdown: "https://aifordevs.org/glossary/reranking.md"
publisher: "AI for Devs"
license: "https://aifordevs.org/reuse"
attribution: "Credit AI for Devs and link to https://aifordevs.org/glossary#reranking"
---

# Reranking

Reranking is a second retrieval pass that rescores a shortlist of candidates with a slower, more accurate model and keeps the best few. The first pass can favor recall because the reranker sets the final order.

A reranker scores the query and each passage together, so it catches relevance that separate embeddings miss, at the cost of added latency per candidate. Nogueira and Cho (2019) reported a 27% relative gain in MRR@10 on MS MARCO with BERT as the reranker.

## Example

Anthropic's Contextual Retrieval test took the top 150 chunks, reranked them with Cohere's model, and kept 20. Anthropic reports that the full stack cut top-20 retrieval failures by 67%, from 5.7% to 1.9%.

## Source

[Nogueira and Cho, Passage Re-ranking with BERT (2019)](https://arxiv.org/abs/1901.04085)

## Related terms

- [RAG](https://aifordevs.org/glossary#rag)
- [Hybrid search](https://aifordevs.org/glossary#hybrid-search)
- [Chunking](https://aifordevs.org/glossary#chunking)
- [Vector database](https://aifordevs.org/glossary#vector-database)

## Read the article

[What is a vector database? HNSW, IVF, and when to skip one](https://aifordevs.org/articles/what-is-a-vector-database)

## Cite this term

AI for Devs. "Reranking." https://aifordevs.org/glossary#reranking

- Page: https://aifordevs.org/glossary#reranking
- Markdown: https://aifordevs.org/glossary/reranking.md
- Reuse: Quote or summarize with a link to this page. Terms: https://aifordevs.org/reuse
- Publisher: AI for Devs