Applied AI Series - RAG Better Results with Re-ranking
· 11 min read
Re-ranking in Retrieval-Augmented Generation (RAG) refines the documents retrieved in response to a user query, ensuring that only the most relevant and contextually appropriate ones are passed to the generation model. This step enhances response accuracy, handles ambiguity, and improves overall result quality by prioritizing the best matches for the query, ultimately leading to more precise and coherent AI-generated answers.