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OttomanNLP/CHURRO-Ottoman-Turkish-Subset

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@inproceedings{semnani-etal-2025-churro,
    title = "{CHURRO}: Making History Readable with an Open-Weight Large Vision-Language Model for High-Accuracy, Low-Cost Historical Text Recognition",
    author = "Semnani, Sina  and
      Zhang, Han  and
      He, Xinyan  and
      Tekgurler, Merve  and
      Lam, Monica",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2025.emnlp-main.1763/",
    doi = "10.18653/v1/2025.emnlp-main.1763",
    pages = "34777--34824",
    ISBN = "979-8-89176-332-6",
    abstract = "Accurate text recognition for historical documents can greatly advance the study and preservation of cultural heritage. Existing vision-language models (VLMs), however, are designed for modern, standardized texts and are not equipped to read the diverse languages and scripts, irregular layouts, and frequent degradation found in historical materials.This paper presents CHURRO, a 3B-parameter open-weight VLM specialized for historical text recognition. The model is trained on CHURRO-DS, the largest historical text recognition dataset to date. CHURRO-DS unifies 155 historical corpora comprising 99,491 pages, spannin

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dataset_licence({ "id": "OttomanNLP/CHURRO-Ottoman-Turkish-Subset" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0