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| title: Video STaR Dataset | |
| emoji: π’ | |
| colorFrom: pink | |
| colorTo: green | |
| sdk: gradio | |
| sdk_version: 4.29.0 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| # Video-STaR 1M Dataset Demo | |
| [π₯οΈ [Website](https://orrzohar.github.io/projects/video-star/)] | |
| [π° [Paper](https://arxiv.org/abs/2407.06189)] | |
| [π« [Code](https://github.com/orrzohar/Video-STaR)] | |
| [π€ [dataset](https://huggingface.co/datasets/orrzohar/Video-STaR)] | |
| ## βοΈ Citation | |
| If you find our paper and code useful in your research, please consider giving a star :star: and citation :pencil:. | |
| ```BibTeX | |
| @inproceedings{zohar2024videostar, | |
| title = {Video-STaR: Self-Training Enables Video Instruction Tuning with Any Supervision}, | |
| author = {Zohar, Orr and Wang, Xiaohan and Bitton, Yonatan and Szpektor, Idan and Yeung-levy, Serena}, | |
| year = {2024}, | |
| booktitle = {arXiv preprint arXiv:2407.06189}, | |
| } | |
| ``` |