In “Assessing Copilot’s Semantic Depth in Classical Arabic: A Mixed-Methods Evaluation Using Alfiyah ibn Malik and Nadham Al-Imrithy” (Lisania: Journal of Arabic Education and Literature), Nely Rahmawati Zaimah (Sekolah Tinggi Agama Islam Al-Anwar Rembang) and others “evaluated how accurately [Microsoft] Copilot interpreted and understood the advanced Arabic prose from the intricate works of Alfiyah ibn Malik and Nadham Al-Imrithy . . . using a mixed-method approach under the Collect-Measure-Repeat (CMR) framework of Responsible AI.”
In “Determining the meter of classical Arabic poetry using deep learning: a performance analysis” (Frontiers in Artificial Intelligence), A. M. Mutawa ( Kuwait University) and Ayshah Alrumaih (University of Hamburg) utilized “a deep learning-based approach . . . to accurately determine the meter of Arabic poetry using TensorFlow and a large dataset” using “multiple deep learning architectures, including long short-term memory (LSTM), gated recurrent units (GRU), and bidirectional long short-term memory (Bi-LSTM).”
