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IIT Bombay
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Retrieval-augmented reasoning can boost LRM accuracy by up to 60% during test-time scaling, transforming how models handle complex problem-solving.
Chain-of-Agents can reason more accurately over long contexts by processing information chunks in an order determined by Chow-Liu dependency trees, rather than relying on default or semantic similarity.
