{
 "id": "yztian/PRIM",
 "owner": "yztian",
 "name": "PRIM",
 "downloads": 34,
 "likes": 0,
 "last_modified": "2025-11-01T13:58:53.000Z",
 "stated_licence": "mit",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
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 "licence_files": [],
 "sources": [],
 "gated": "auto",
 "tasks": [
  "translation"
 ],
 "citation": "@inproceedings{tian-etal-2025-prim,\n    title = \"{PRIM}: Towards Practical In-Image Multilingual Machine Translation\",\n    author = \"Tian, Yanzhi  and\n      Liu, Zeming  and\n      Liu, Zhengyang  and\n      Feng, Chong  and\n      Li, Xin  and\n      Huang, Heyan  and\n      Guo, Yuhang\",\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.691/\",\n    pages = \"13693--13708\",\n    ISBN = \"979-8-89176-332-6\",\n    abstract = \"In-Image Machine Translation (IIMT) aims to translate images containing texts from one language to another. Current research of end-to-end IIMT mainly conducts on synthetic data, with simple background, single font, fixed text position, and bilingual translation, which can not fully reflect real world, causing a significant gap between the research and practical conditions. To facilitate research of IIMT in real-world scenarios, we explore Practical In-Image Multilingual Machine Translation (IIMMT). In order to convince the lack of publicly available data, we annotate the PRIM dataset, which contains real-world captured one-line text images with complex background, various fonts, diverse text positions, and sup",
 "signal": "permissive",
 "reason": "The declared licence (mit) is classified as permissive.",
 "revision": "58c88a8a56d5cfd29892dfee2819d08c327a1748",
 "stated_evidence": "https://huggingface.co/datasets/yztian/PRIM/blob/58c88a8a56d5cfd29892dfee2819d08c327a1748/README.md",
 "file_evidence": "https://huggingface.co/datasets/yztian/PRIM/tree/58c88a8a56d5cfd29892dfee2819d08c327a1748",
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}