{
 "id": "smksaha/apt-eval",
 "owner": "smksaha",
 "name": "apt-eval",
 "downloads": 281,
 "likes": 3,
 "last_modified": "2025-11-07T17:19:19.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "text-classification",
  "feature-extraction"
 ],
 "citation": "@inproceedings{saha-feizi-2025-almost,\n    title = \"Almost {AI}, Almost Human: The Challenge of Detecting {AI}-Polished Writing\",\n    author = \"Saha, Shoumik  and\n      Feizi, Soheil\",\n    booktitle = \"Findings of the Association for Computational Linguistics: ACL 2025\",\n    month = jul,\n    year = \"2025\",\n    address = \"Vienna, Austria\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2025.findings-acl.1303/\",\n    pages = \"25414--25431\",\n    ISBN = \"979-8-89176-256-5\",\n    abstract = \"The growing use of large language models (LLMs) for text generation has led to widespread concerns about AI-generated content detection. However, an overlooked challenge is AI-polished text, where human-written content undergoes subtle refinements using AI tools. This raises a critical question: should minimally polished text be classified as AI-generated? Such classification can lead to false plagiarism accusations and misleading claims about AI prevalence in online content. In this study, we systematically evaluate *twelve* state-of-the-art AI-text detectors using our **AI-Polished-Text Evaluation (APT-Eval)** dataset, which contains $15K$ samples refined at varying AI-involvement levels. Our findings reveal that detectors frequently flag even minimally polished text as AI-generated, struggle to differentiate between degrees of AI involvement, and exhibit biases against older and smaller models. These limitations highlight the urgent need for m",
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 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "1a183126ec24791c14c3a3254e8cdb5c58935d27",
 "stated_evidence": "https://huggingface.co/datasets/smksaha/apt-eval/blob/1a183126ec24791c14c3a3254e8cdb5c58935d27/README.md",
 "file_evidence": "https://huggingface.co/datasets/smksaha/apt-eval/tree/1a183126ec24791c14c3a3254e8cdb5c58935d27",
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}