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AraGPT2: Pre-Trained Transformer for Arabic Language Generation

arXiv ·

The paper introduces AraGPT2, a suite of pre-trained transformer models for Arabic language generation, with the largest model (AraGPT2-mega) containing 1.46 billion parameters. Trained on a large Arabic corpus of internet text and news, AraGPT2-mega demonstrates strong performance in synthetic news generation and zero-shot question answering. To address the risk of misuse, the authors also released a discriminator model with 98% accuracy in detecting AI-generated text. Why it matters: This release of both the model and discriminator fills a critical gap in Arabic NLP and encourages further research and applications in the field.

PROUD MOMENT: World-class accolade to AMRC’s Prof. Marco Amabili

TII ·

Professor Marco Amabili, advisor at the Advanced Materials Research Center (AMRC), received the 'Cataldo Agostinelli and Angiola Gili Agostinelli' International Prize from the Lincei National Academy of Sciences of Italy. The award recognizes Prof. Amabili's research in mechanical vibrations, composite structures, and vascular biomechanics. He received the award in Rome from Nobel laureate Professor Giorgio Parisi. Why it matters: The recognition highlights the growing international visibility of UAE-based researchers and the increasing commitment of UAE institutions like TII to deep-tech research.