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This paper identifies 'vector search dilution' in RAG systems when scaling to large heterogeneous document collections, where accuracy dropped from 75% to 40% in a real-world deployment. The proposed MASDR-RAG method uses domain scoping via organizational metadata before retrieval, improving P@10 from 0.77 to 0.86 with low cost and easy deployment.
This paper identifies 'vector search dilution' in RAG systems when scaling to large, heterogeneous document collections, and proposes MASDR-RAG, a domain-scoped retrieval approach that significantly improves retrieval accuracy by leveraging organizational metadata.