{
 "id": "docling-project/SynthChartNet",
 "owner": "docling-project",
 "name": "SynthChartNet",
 "downloads": 1714,
 "likes": 16,
 "last_modified": "2025-07-15T14:16:24.000Z",
 "stated_licence": "cdla-permissive-2.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "image-text-to-text"
 ],
 "citation": "@article{nassar2025smoldocling,\n  title={SmolDocling: An ultra-compact vision-language model for end-to-end multi-modal document conversion},\n  author={Nassar, Ahmed and Marafioti, Andres and Omenetti, Matteo and Lysak, Maksym and Livathinos, Nikolaos and Auer, Christoph and Morin, Lucas and de Lima, Rafael Teixeira and Kim, Yusik and Gurbuz, A Said and others},\n  journal={arXiv preprint arXiv:2503.11576},\n  year={2025}\n}\n@inproceedings{lysak2023optimized,\n  title={Optimized table tokenization for table structure recognition},\n  author={Lysak, Maksym and Nassar, Ahmed and Livathinos, Nikolaos and Auer, Christoph and Staar, Peter},\n  booktitle={International Conference on Document Analysis and Recognition},\n  pages={37--50},\n  year={2023},\n  organization={Springer}\n}",
 "signal": "unclear",
 "reason": "The checks could not identify a recognised licence ID in the dataset's metadata.",
 "revision": "b913ef98a3d45f6136465963ddc71a7a6b0e1728",
 "stated_evidence": "https://huggingface.co/datasets/docling-project/SynthChartNet/blob/b913ef98a3d45f6136465963ddc71a7a6b0e1728/README.md",
 "file_evidence": "https://huggingface.co/datasets/docling-project/SynthChartNet/tree/b913ef98a3d45f6136465963ddc71a7a6b0e1728",
 "card_nc": false
}