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Skip the training and the hyperparameter tuning: Swift Sampling uses Taylor series to find the most informative frames in a video, beating existing methods with a 30x reduction in overhead.
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.
