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AOT: Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models

arXiv Project Page

overview

teaser

Quick Start

1. Create the environment

2. Download or place checkpoints

3. Perform the Token Reduction Evaluation

Citation

If you use AOT in academic or industrial research, please cite:

@article{li2026token,
  title={Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models},
  author={Li, Jinlong and Jiang, Liyuan and Zhang, Haonan and Sebe, Nicu},
  journal={arXiv preprint arXiv:2603.01400},
  year={2026}
}

Related Project

License

  • Code: MIT License (see LICENSE).
  • Model weights: Adobe Research License (see LICENSE-WEIGHTS). The model weights are not covered by the MIT License.

Acknowledgements

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CVPR2026 Token Reduction via Local and Global Contexts Optimization for Efficient Video Large Language Models

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