@inproceedings{sakhovskiy-etal-2026-inksight,
    title = "{I}nk{S}ight: Towards {AI}-Aided Historical Manuscript Analysis",
    author = "Sakhovskiy, Andrey  and
      Ulitin, Ivan  and
      Bojarskaja, Emilia  and
      Kokh, Vladimir  and
      Murtazin, Ruslan  and
      Novopoltsev, Maxim  and
      Budennyy, Semen",
    editor = "Croce, Danilo  and
      Leidner, Jochen  and
      Moosavi, Nafise Sadat",
    booktitle = "Proceedings of the 19th Conference of the {E}uropean Chapter of the {A}ssociation for {C}omputational {L}inguistics (Volume 3: System Demonstrations)",
    month = mar,
    year = "2026",
    address = "Rabat, Marocco",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-eacl/2026.eacl-demo.20/",
    pages = "271--281",
    ISBN = "979-8-89176-382-1",
    abstract = "Large-scale scientific research on historical documents {---} particularly medieval Arabic manuscripts {---} remains challenging due to the need for advanced paleographic and linguistic training, the large volume of hand-written materials, and the absence of assisting software. In this paper, we propose InkSight, the first end-to-end Arabic manuscript analysis tool for manuscript-based analytics and research hypothesis testing. InkSight integrates three key components: (i) an Optical Character Recognition (OCR) module utilizing a Large Visual Language Model (LVLM); (ii) a lightweight document indexing and information retrieval module that enables query-based evidence retrieval from book-length manuscripts; and (iii) a flexible Large Language Model (LLM) prompting interface factually grounded to the given manuscript via Retrieval-Augmented Generation (RAG). Empirical evaluation on the existing KITAB OCR benchmark and our in-house dataset of ancient Arabic manuscripts has revealed that historical research can be effectively supported using smaller fine-tuned LVLMs without relying on larger proprietary models. The live web demo for InkSight is available freely at: https://inksight.ru and the source code for InkSight is publicly available at Github: https://github.com/ds-hub-sochi/InkSight-tool."
}