Arabic Natural Language Generation

Arabic Natural Language Generation (NLG) research focuses on developing computational models capable of producing human-quality Arabic text for various applications. Current efforts concentrate on improving large language models (LLMs), particularly through enhanced training data (including dialectal variations) and more rigorous evaluation benchmarks that assess trustworthiness and performance across diverse tasks. These advancements leverage transformer-based architectures like T5 and BERT, aiming to overcome challenges posed by the linguistic complexity and resource scarcity in Arabic NLP. The resulting improvements in Arabic NLG have significant implications for both advancing fundamental research in multilingual NLP and enabling practical applications such as machine translation, story generation, and chatbot development.