How to Evaluate Retrieval Quality in RAG Pipelines (part 2): Mean Reciprocal Rank (MRR) and Average Precision (AP)

The article discusses advanced methods for assessing retrieval quality in Retrieval-Augmented Generation (RAG) pipelines using binary, order-aware metrics such as Mean Reciprocal Rank (MRR) and Average Precision (AP). These measures provide a more nuanced evaluation of how effectively the retrieval component ranks relevant documents, emphasizing the importance of both relevance and position in the retrieval process. Implementing these metrics enhances the ability to optimize RAG systems for improved accuracy and user experience, marking a significant step forward in the development of more reliable and precise AI-driven information retrieval frameworks.