| --- |
| license: cc-by-4.0 |
| --- |
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| # LIBAD |
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| LIBAD is the dataset accompanying the paper **"LIBAD: A Multimodal Anomaly Detection Benchmark for Li-Ion Battery Electrode Manufacturing"**. |
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| **GitHub:** [LIBAD](https://github.com/evenrose/LIBAD) |
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| **Paper:** [arXiv:2608.07958](https://arxiv.org/abs/2608.07958) |
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| The repository contains: |
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| * `LIBAD.zip`: the LIBAD multimodal anomaly detection dataset. |
| * `splits.zip`: the 10 official data splits used in our experiments. |
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| ## Usage |
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| Download and extract both archives into the `dataset/` directory of the official code repository: |
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| ```text |
| dataset/ |
| ├── LIBAD/ |
| └── splits/ |
| ``` |
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| The 10 official splits correspond to the following dataset seeds: |
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| ```text |
| 347, 725, 1245, 4012, 4589, 5021, 5678, 6234, 6789, 7345 |
| ``` |
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| Code and experimental instructions are available in the official GitHub repository: |
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| ## Citation |
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| If you use LIBAD in your research, please cite the corresponding paper: |
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| ```bibtex |
| @misc{sui2026libadmultimodalanomalydetection, |
| title={LIBAD: A Multimodal Anomaly Detection Benchmark for Li-Ion Battery Electrode Manufacturing}, |
| author={Wenbo Sui and Daniel Lichau and Harold Phelippeau and Zhao Liu}, |
| year={2026}, |
| eprint={2608.07958}, |
| archivePrefix={arXiv}, |
| primaryClass={cs.CV}, |
| url={https://arxiv.org/abs/2608.07958}, |
| } |
| ``` |
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|
