Researchers at MBZUAI have developed a new method for controllable poetry generation in Arabic and its dialects, moving beyond traditional analysis tasks for Arabic poetry within Large Language Models (LLMs). They introduce a large-scale, instruction-based dataset in Modern Standard Arabic (MSA) and various Arabic dialects, enabling LLMs to perform tasks like writing, revising, and continuing poems based on user criteria. Experiments show that fine-tuning LLMs on this dataset results in models capable of generating poetry aligned with user requirements, validated by automated metrics and human evaluation. Why it matters: This work represents a significant advancement in Arabic Natural Language Processing, offering tools for creative expression and cultural preservation while opening new avenues for user-guided content generation in culturally rich text forms.
MBZUAI researchers release 'Fann or Flop', a new benchmark for evaluating Arabic poetry understanding in LLMs. The benchmark covers 12 historical eras and 14 poetic genres, assessing semantic understanding, metaphor interpretation, and cultural context. Evaluation of state-of-the-art LLMs reveals challenges in poetic understanding despite strong performance on standard Arabic benchmarks.
The paper introduces AraPoemBERT, an Arabic language model pretrained exclusively on 2.09 million verses of Arabic poetry. AraPoemBERT was evaluated against five other Arabic language models on tasks including poet's gender classification (99.34% accuracy) and poetry sub-meter classification (97.79% accuracy). The model achieved state-of-the-art results in these and other downstream tasks, and is publicly available on Hugging Face. Why it matters: This specialized model advances Arabic NLP by providing a new state-of-the-art tool tailored for the nuances of classical Arabic poetry.
Inception, Cerebras, and MBZUAI have released Jais 2, a 70 billion parameter open-weight Arabic LLM. Jais 2 is trained on an Arabic-first dataset and features a redesigned architecture for stronger reasoning and fluency across Arabic dialects and English. It integrates a safety-first framework and demonstrates capabilities in understanding Arabic poetry, culture, and social media tone. Why it matters: Jais 2 addresses the historical underrepresentation of Arabic in AI by providing a culturally and linguistically faithful model, potentially accelerating innovation across the region.