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The paper proposes LoHi, a training-free framework that jointly allocates frames, resolution, and front-end decoding latency for long-video understanding with VLMs, combining dense low-resolution video streams with sparse high-resolution frames, improving accuracy by up to 10.6 points over baselines and reducing decoding latency up to 7x on hour-long videos.