Papers by Daoze Zhang

1 papers
Sharper and Faster mean Better: Towards More Efficient Vision-Language Model for Hour-scale Long Video Understanding (2025.acl-long)

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Challenge: Existing multimodal large language models (LLMs) have shown impressive performance on the video understanding task, but extremely long videos still pose significant challenges to their context length, memory consumption, and computational complexity.
Approach: They propose a vision-language model named Sophia for long video understanding which can efficiently handle hour-scale long videos.
Outcome: The proposed model exhibits competitive performance compared to existing video understanding baselines across various benchmarks for long video understanding with reduced time and memory consumption.

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