YallaMorph is introduced, a large-scale benchmark for Arabic morphological generation covering verbs, nouns, adjectives, their cliticized forms, and invalid configurations over 600K benchmark entries, which shows that Arabic morphological generation remains difficult.
Abstract
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 entries. Results show that Arabic morphological generation remains difficult, especially for cliticized, unseen, and morphologically rare forms.
A baseline morphological analyzer is built by evaluating a wider range of supervised systems, including lexicon-lookup, Conditional Random Fields (CRFs), full fine-tuning of Arabic PLMs, and AraT5 configurations, to demonstrate severe limitations in current capabilities.
A resource-efficient adaptation of the English-pretrained ModernBERT for Arabic, employing continued pretraining on large Arabic corpora followed by lightweight head-only fine-tuning with a frozen encoder, demonstrating that modern English encoder architectures can be efficiently transferred to Arabic through language-...
Ahmed Samy Eldamaty, M. Abdelrahman, Mohamed Mostafa Ibrahim Elbehery et al.· International Conference on...· 0 citations
Part-of-speech (POS) tagging in Arabic is hard because its rich root-and-pattern morphology and the absence of short vowels make one unvoweled string compatible with many categories. This paper presents Jawhar, a hybrid framework that couples a high-performance morphological analyser with contextual reranking using a p...
Mohamed Bouzahir, A. A. Abdelouahad, M. Nabil· Information· 0 citations
Retrieval-Augmented Generation (RAG) has become a standard technique to ground large language model outputs in external knowledge. However, evaluating RAG systems for Arabic remains problematic because traditional lexical metrics such as ROUGE and BLEU were designed for English, a language with limited morphological va...
Ahmed Ali Al-Ansi, Khalil Al-Wagih· 2026 6th International Confe...· 0 citations
The findings support a diagnostic rather than leaderboard interpretation: the apparent benefit of Arabic XTTS adaptation depends materially on the evaluation metric, checkpoint, and evaluator.
We present edition 2.0 of the PARSEME multilingual corpus annotated for multiword expressions (MWEs), resulting from efforts of the PARSEME community towards universality-driven modeling of idiomaticity. With respect to previous editions, we extend the annotation scope to all syntactic MWE categories: verbal, nominal,...
Agata Savary, Manon Scholivet, C. Ramisch et al.· International Conference on...· 3 citations
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