Zero-Shot Learning For Multilingual Document Classification In Low-Resource Languages

Document classification in low-resource languages remains a critical challenge due to the scarcity of annotated datasets, language-specific resources, and linguistic tools. This study investigates the effectiveness of zero-shot learning (ZSL) for multilingual document classification, with a specific...

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Bibliografski detalji

Glavni autori:	Nasios Orinos, Quedevo Onola, Ong Ben Chistoff
Format:	Artigo
Jezik:	Inglês
Izdano:	Universitas Sains dan Teknologi Komputer 2025-12-01
Serija:	Journal of Technology Informatics and Engineering
Teme:	zero-shot learning (zsl) multilingual document classification low-resource languages xlm-roberta (xlm-r) multilingual t5 (mt5)
Online pristup:	https://jtie.stekom.ac.id/index.php/jtie/article/view/446
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