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RAG models struggle to use retrieved knowledge even when it's relevant, but GuarantRAG's two-stage generation and joint decoding boosts accuracy by 12% and slashes hallucinations by 16%.
LRMs can be made more efficient and accurate by strategically adjusting their output length based on task difficulty, leading to a better accuracy-length trade-off.