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LLMs improve reading order reconstruction for historical Armenian newspapers

By PulseAugur Editorial · [2 sources] ·

Researchers have developed a novel method for reconstructing the reading order of historical Armenian newspapers, which present challenges due to complex layouts and limited linguistic resources. Their hybrid approach combines semantic zone detection with a generative LLM, achieving a 76% reduction in ordering errors compared to baseline methods. This technique is designed to accelerate data annotation for under-resourced languages and includes a specialized Tesseract OCR model for historical Armenian print. AI

IMPACT Enhances accessibility of historical documents and accelerates data annotation for under-resourced languages.

RANK_REASON The item is a research paper detailing a new method for document analysis using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 2 sources. How we write summaries →

LLMs improve reading order reconstruction for historical Armenian newspapers

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The item is a research paper detailing a new method for document analysis using LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [2]

  1. arXiv cs.CV TIER_1 English(EN) · Chahan Vidal-Gor\`ene (CJM, LIPN), Nadi Tomeh (LIPN), Victoria Khurshudyan (Inalco, SeDyL) ·

    Semantic-Guided Reading Order Reconstruction in Historical Armenian Newspapers with LLMs

    arXiv:2607.00596v1 Announce Type: new Abstract: This paper addresses reading order reconstruction in historical Armenian newspapers, which combine complex layouts with limited language resources. We introduce a new annotated dataset of 66 pages and compare geometric heuristics, Y…

  2. arXiv cs.CV TIER_1 English(EN) · Victoria Khurshudyan ·

    Semantic-Guided Reading Order Reconstruction in Historical Armenian Newspapers with LLMs

    This paper addresses reading order reconstruction in historical Armenian newspapers, which combine complex layouts with limited language resources. We introduce a new annotated dataset of 66 pages and compare geometric heuristics, YOLO-based layout parsing, an end-to-end document…

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