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YallaMorph: A Benchmark for Evaluating Arabic Morphological Generation in Large Language Models
Arabic morphology remains challenging for large language models, since fluent generation does not guarantee accurate morphosyntactic control. Existing Arabic evaluations mainly target downstream tasks and do not directly test controlled morphological generation from explicit lexical and feature-based input. We introduce YallaMorph, a large-scale benchmark for Arabic morphological generation covering verbs, nouns, adjectives, their cliticized forms, and invalid configurations. We evaluate multilingual and Arabic-oriented LLMs under diacritized and undiacritized settings over 600K benchmark entr
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-09T13:31:56.000Z
First collected: 2026-09-20T19:32:24.350Z. This is not the publication date.