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Retrieval fusion, a popular technique for boosting recall in RAG systems, surprisingly fails to improve end-to-end accuracy in a production setting with realistic constraints, even *decreasing* Hit@10 in some cases.
Current RAG evaluation metrics miss critical enterprise failure modes, but this new framework exposes actionable tradeoffs in multi-turn workflows by evaluating retrieval, grounding, utility, precision, and case alignment.
