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  - **`coordinate.tar`**: To facilitate faster training for geometric models, we provide pre-extracted C-alpha (Cα) coordinates. This reduces I/O overhead by focusing on the protein backbone trajectory.
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  - **`localization/`**: Includes both the original raw labels and our integrated 20-class fine-grained labels. These annotations are specifically curated to evaluate model performance across diverse subcellular compartments, whose processing details can be found in our paper.
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  - **`coordinate.tar`**: To facilitate faster training for geometric models, we provide pre-extracted C-alpha (Cα) coordinates. This reduces I/O overhead by focusing on the protein backbone trajectory.
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  - **`localization/`**: Includes both the original raw labels and our integrated 20-class fine-grained labels. These annotations are specifically curated to evaluate model performance across diverse subcellular compartments, whose processing details can be found in our paper.
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+ ### 📜 Citation
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+ If you use this dataset and benchmark CAPSUL in your research, please cite:
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+
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+ ```
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+ @article{hu2026capsul,
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+ title={CAPSUL: A Comprehensive Human Protein Benchmark for Subcellular Localization},
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+ author={Hu, Yicheng and Lin, Xinyu and Li, Shulin and Wang, Wenjie and Zhu, Fengbin and Feng, Fuli},
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+ journal={arXiv preprint arXiv:2603.18571},
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+ year={2026}
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+ }
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+ ```
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+