{
 "id": "whybe-choi/en-vdr-hn",
 "owner": "whybe-choi",
 "name": "en-vdr-hn",
 "downloads": 529,
 "likes": 1,
 "last_modified": "2026-10-21T04:21:53.000Z",
 "stated_licence": "other",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "image-to-text",
  "sentence-similarity"
 ],
 "citation": "@article{choi2026kovre,\n  title={KoVRE: Training an Efficient Embedding Model for Korean Visual Document Retrieval},\n  author={Choi, Yongbin and Shim, Gyuho and Jang, Youngjoon},\n  journal={arXiv preprint arXiv:2608.01389},\n  year={2026}\n}",
 "signal": "unclear",
 "reason": "The checks could not identify a recognised licence ID in the dataset's metadata.",
 "revision": "474f21048d3cc721e03308b4aa60f53941f11e2f",
 "stated_evidence": "https://huggingface.co/datasets/whybe-choi/en-vdr-hn/blob/474f21048d3cc721e03308b4aa60f53941f11e2f/README.md",
 "file_evidence": "https://huggingface.co/datasets/whybe-choi/en-vdr-hn/tree/474f21048d3cc721e03308b4aa60f53941f11e2f",
 "card_nc": false
}