Arabic Dataset

Research on Arabic datasets focuses on developing and improving resources for natural language processing (NLP) tasks in Arabic, a language with unique linguistic challenges and a relative scarcity of high-quality data. Current efforts concentrate on creating diverse benchmarks for evaluating large language models (LLMs) across various domains, including legal, mathematical, and mental health contexts, often employing transformer-based architectures like BERT and its variants. These advancements are crucial for bridging the gap in Arabic NLP resources, enabling the development of more accurate and culturally sensitive AI applications and fostering further research in low-resource language processing.