{
 "id": "pykale/bln600-img-patch",
 "owner": "pykale",
 "name": "bln600-img-patch",
 "downloads": 51,
 "likes": 0,
 "last_modified": "2026-10-26T15:32:17.000Z",
 "stated_licence": "cc-by-nc-nd-4.0",
 "stated_from": "tag",
 "licence_name": null,
 "licence_link": null,
 "file_licence": null,
 "licence_files": [],
 "sources": [],
 "gated": false,
 "tasks": [
  "image-to-text"
 ],
 "citation": "@inproceedings{thomas-etal-2026-image,\n    title = \"Image-Informed Post-{OCR} Correction with Vision-Language Models\",\n    author = \"Thomas, Alan  and\n      Liu, Xianyuan  and\n      Lu, Haiping  and\n      Gaizauskas, Robert J.\",\n    editor = \"Lee, Hung-Yi  and\n      Dev, Sunipa  and\n      Li, Jessy  and\n      Elliott, Desmond\",\n    booktitle = \"Findings of the {A}ssociation for {C}omputational {L}inguistics: {EMNLP} 2026\",\n    month = oct,\n    year = \"2026\",\n    address = \"Budapest, Hungary\",\n    publisher = \"Association for Computational Linguistics\",\n    url = \"https://aclanthology.org/2026.findings-emnlp.60/\",\n    pages = \"1224--1237\",\n    ISBN = \"979-8-89176-462-0\",\n    abstract = \"Improving the quality of OCR transcriptions is crucial for researchers working with digital archives, as OCR errors hinder readability and downstream NLP tasks. While prior work has focused on seq2seq neural machine translation and, more recently, prompt-based approaches with large language models (LLMs), these methods rely solely on text, overlooking the visual characteristics of source documents. In this work, we explore the potential of vision-language models (VLMs) for post-OCR correction to evaluate the impact of integrating visual information. We conduct experiments on the BLN600 dataset of 19th-century newspaper articles, comparing Llama 3.2 Vision and Qwen 2.5 VL to their text-only LLM counterparts. Our results show that VLMs significantly outperform LLMs, achieving approximately 90{\\%}",
 "signal": "restrictive",
 "reason": "The declared licence (cc-by-nc-nd-4.0) is classified as having use restrictions.",
 "revision": "72944d6472bd37f5b87d0e131761c0cb6c774d31",
 "stated_evidence": "https://huggingface.co/datasets/pykale/bln600-img-patch/blob/72944d6472bd37f5b87d0e131761c0cb6c774d31/README.md",
 "file_evidence": "https://huggingface.co/datasets/pykale/bln600-img-patch/tree/72944d6472bd37f5b87d0e131761c0cb6c774d31",
 "card_nc": false
}