SOURCE-LINKED INTELLIGENCE

Text Restoration of Ancient Documents with Language Models

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Purpose - This study investigates the feasibility of restoring missing text caused by physical lacunae in damaged ancient manuscripts using language models. Methodology - The study proposes different scenarios to replicate real-world conditions. Language models of different architectures are applied according to their suitability to each scenario. We also propose several decoding strategies that further enhance performance and address the discrepancy between lacuna boundaries and the models' tokenization schemes. Findings - The results reveal that text restoration of these documents cannot be

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