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SciGA: A Comprehensive Dataset for Designing Graphical Abstracts in Academic Papers

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Kawada, Takuro, Kitada, Shunsuke, Nemoto, Sota, Iyatomi, Hitoshi
Format:	Preprint
Publié:	2025
Sujets:	Computer Vision and Pattern Recognition Computation and Language Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

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