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Entropy-Aware Dense Pruning not only filters out textual noise but also ensures a comprehensive visual representation, leading to superior performance in vision-language tasks.
Current video MLLMs struggle to grasp fleeting visual events, with top models barely surpassing 39% accuracy on critical momentary tasks.
