Papers by Wenhao Hong

1 papers
MoPrune: Scene-Guided Motion-Aware Token Pruning for Efficient Video Large Language Models (2026.findings-acl)

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Challenge: Prior approaches to token pruning ignore video dynamics and the fact that different scenes exhibit different redundancy patterns.
Approach: They propose a token pruning framework that is train-free and scene-guided to accelerate VideoLLMs by removing redundant visual information from video frames.
Outcome: MoPrune is a training-free, scene-guided and motion-centric token pruning framework for accelerating VideoLLMs.

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