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New AI models tackle newspaper image hierarchy and structure understanding · 2 sources tracked

Researchers have developed two methods for understanding the complex hierarchical structures within newspaper images. One approach uses a modular pipeline combining YOLO for layout detection and LayoutReader for reading order, while the other introduces Tiramisu, a novel transformer-based architecture designed to model document hierarchy iteratively. The study also introduces Finlam La Liberté, a new dataset for evaluating hierarchical information retrieval in historical newspapers, and makes the Tiramisu training code publicly available. AI

IMPACT This research could improve automated digitization and information retrieval for historical documents.

RANK_REASON The cluster contains an academic paper detailing new AI models and a dataset for a specific research task.

Read on arXiv cs.AI →

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

New AI models tackle newspaper image hierarchy and structure understanding · 2 sources tracked

COVERAGE [2]

  1. arXiv cs.AI TIER_1 English(EN) · William Moca\"er, Sol\`ene Tarride, Thomas Constum, Merveilles Agbeti-Messan, Tom Simon, Cl\'ement Chatelain, St\'ephane Nicolas, Pierrick Tranouez, S\'ebastien Cretin, Thierry Paquet ·

    Towards Hierarchical Structure Understanding of Newspaper Images

    arXiv:2607.15082v1 Announce Type: cross Abstract: Understanding newspaper images remains a challenging task due to their complex, nested hierarchical structures and dense, heterogeneous layouts. In this paper, we explore two complementary approaches for newspaper structure unders…

  2. arXiv cs.AI TIER_1 English(EN) · Thierry Paquet ·

    Towards Hierarchical Structure Understanding of Newspaper Images

    Understanding newspaper images remains a challenging task due to their complex, nested hierarchical structures and dense, heterogeneous layouts. In this paper, we explore two complementary approaches for newspaper structure understanding. First, we present a modular bottom-up pip…