Croissant: A Metadata Format for ML-Ready Datasets
<|reference_start|>Croissant: A Metadata Format for ML-Ready Datasets: Data is a critical resource for Machine Learning (ML), yet working with data remains a key friction point. This paper introduces Croissant, a metadata format for datasets that simplifies how data is used by ML tools and frameworks. Croissant makes datasets more discoverable, portable and interoperable, thereby addressing significant challenges in ML data management and responsible AI. Croissant is already supported by several popular dataset repositories, spanning hundreds of thousands of datasets, ready to be loaded into the most popular ML frameworks.<|reference_end|>
@article{akhtar2024croissant:,
    title={Croissant: A Metadata Format for ML-Ready Datasets},
    author={Mubashara Akhtar, Omar Benjelloun, Costanza Conforti, Pieter Gijsbers,
  Joan Giner-Miguelez, Nitisha Jain, Michael Kuchnik, Quentin Lhoest, Pierre
  Marcenac, Manil Maskey, Peter Mattson, Luis Oala, Pierre Ruyssen, Rajat
  Shinde, Elena Simperl, Goeffry Thomas, Slava Tykhonov, Joaquin Vanschoren,
  Jos van der Velde, Steffen Vogler, Carole-Jean Wu},
    journal={arXiv preprint arXiv:2403.19546},
    year={2024},
    doi={10.1145/3650203.3663326},
    archivePrefix={arXiv},
    eprint={2403.19546},
    primaryClass={cs.LG cs.AI cs.DB cs.IR}
}