Query rewriting for RAG: how to improve retrieval accuracy

What this post added

This post introduces query rewriting as a technique to improve retrieval accuracy within RAG pipelines by transforming user queries to better match dataset language, addressing issues like vocabulary mismatch and ambiguous intents. It details techniques such as query expansion, decomposition, paraphrasing, multi-query generation, and step-back prompting, and provides implementation steps involving query normalization, LLM-based rewriting, and retrieval.