AraGenre 2026: A Hierarchical Definition-Guided Arabic Genre Classification Shared Task
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Computer Science > Computation and Language
Title:AraGenre 2026: A Hierarchical Definition-Guided Arabic Genre Classification Shared Task
Abstract:AraGenre is a shared task on hierarchical, definition-guided Arabic genre classification, motivated by the limited availability of annotated data in Arabic and other low-resource languages. Systems assign each Arabic text segment both a broad communicative genre and a fine-grained specific genre. The released training and development sets contain limited, primarily synthetic and controlled examples, whereas the hidden final benchmark contains noisier naturally occurring text spanning Modern Standard Arabic, Classical Arabic, and multiple dialects. Participants received natural-language definitions for 74 previously unseen specific genres, creating a zero-shot label generalisation setting in which systems had to infer class semantics rather than memorise fixed label-feature associations. The task attracted 46 registrations and 373 submissions, with 17 teams completing the final evaluation. Thakaa ranked first with a Hierarchical Macro F1 of 0.7352, followed by HoangPhong (HP) with 0.7169 and NAMAA with 0.7013. The results show strong broad-genre recognition but a substantial gap in fine-grained classification under linguistic and domain variation.
| Comments: | 8 pages |
| Subjects: | Computation and Language (cs.CL) |
| Cite as: | arXiv:2609.27387 [cs.CL] |
| (or arXiv:2609.27387v1 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2609.27387
arXiv-issued DOI via DataCite (pending registration)
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| Journal reference: | The 4th ArabicNLP conference at EMNLP 2026 |
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