{
 "id": "VLM2Vec/MMEB-V3",
 "owner": "VLM2Vec",
 "name": "MMEB-V3",
 "downloads": 2332,
 "likes": 9,
 "last_modified": "2026-08-06T04:01:20.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "feature-extraction",
  "image-to-text",
  "text-to-image"
 ],
 "citation": "@article{huang2026mmeb,\n  title={MMEB-V3: Measuring the Performance Gaps of Omni-Modality Embedding Models},\n  author={Huang, Haohang and Lu, Xuan and Su, Mingyi and Zhang, Xuan and Jiang, Ziyan and Nie, Ping and Zou, Kai and Pfister, Tomas and Chen, Wenhu and Zhang, Wei and others},\n  journal={arXiv preprint arXiv:2604.23321},\n  year={2026}\n}",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "4a5560b2b64384204b6fea8a82ea986eba51f5aa",
 "stated_evidence": "https://huggingface.co/datasets/VLM2Vec/MMEB-V3/blob/4a5560b2b64384204b6fea8a82ea986eba51f5aa/README.md",
 "file_evidence": "https://huggingface.co/datasets/VLM2Vec/MMEB-V3/tree/4a5560b2b64384204b6fea8a82ea986eba51f5aa",
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}