{
 "id": "MLNTeam-Unical/OpenTuringBench",
 "owner": "MLNTeam-Unical",
 "name": "OpenTuringBench",
 "downloads": 262,
 "likes": 1,
 "last_modified": "2025-11-11T05:19:43.000Z",
 "stated_licence": "cc-by-nc-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-classification",
  "token-classification",
  "zero-shot-classification",
  "text-generation",
  "sentence-similarity",
  "summarization",
  "translation",
  "feature-extraction",
  "question-answering"
 ],
 "citation": "@inproceedings{la-cava-tagarelli-2025-openturingbench,\n    title = \"{O}pen{T}uring{B}ench: An Open-Model-based Benchmark and Framework for Machine-Generated Text Detection and Attribution\",\n    author = \"La Cava, Lucio  and\n      Tagarelli, Andrea\",\n    editor = \"Christodoulopoulos, Christos  and\n      Chakraborty, Tanmoy  and\n      Rose, Carolyn  and\n      Peng, Violet\",\n    booktitle = \"Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing\",\n    month = nov,\n    year = \"2025\",\n    address = \"Suzhou, China\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2025.emnlp-main.1354/\",\n    doi = \"10.18653/v1/2025.emnlp-main.1354\",\n    pages = \"26666--26682\",\n    ISBN = \"979-8-89176-332-6\" \n}",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-4.0) is classified as having use restrictions.",
 "revision": "3cea15f294e074620586565b6987c8df3b807ada",
 "stated_evidence": "https://huggingface.co/datasets/MLNTeam-Unical/OpenTuringBench/blob/3cea15f294e074620586565b6987c8df3b807ada/README.md",
 "file_evidence": "https://huggingface.co/datasets/MLNTeam-Unical/OpenTuringBench/tree/3cea15f294e074620586565b6987c8df3b807ada",
 "card_nc": false
}