7 stories tagged Arabic
The Technology Innovation Institute (TII) released Falcon-Emirati, an open-source AI language model built on Falcon-40B that understands and generates Emirati Arabic, including its unique dialect and cultural nuances, making AI more accessible to Arabic speakers in the UAE.
A new study on ArXiv provides the first holistic assessment of the carbon footprint of Noor, a very large Arabic language model. The research finds that focusing only on training emissions dramatically undercounts the total environmental impact, as data collection, preprocessing, and deployment also contribute significantly.
MBZUAI, Cerebras, and Inception have released Jais 2, a family of open large language models optimized for Arabic. The family includes a 70-billion-parameter model, the largest open Arabic-centric LLM trained from scratch, and an 8-billion-parameter variant. Both models use a custom Arabic-centric vocabulary for efficient training and inference.
Researchers introduced AHA-Memes, the first large-scale Arabic hateful meme benchmark with fine-grained, multi-label annotations. This dataset enables more precise detection of hate speech in Arabic memes, addressing a critical gap in online safety for Arabic-speaking communities.
Researchers from the University of Washington and NYU Abu Dhabi introduced CAMMAR, a representation learning framework that organizes Arabic meanings into nested lexical, cultural, and metaphorical embedding subspaces. This approach addresses 'semantic smearing' in current Arabic language models and could improve translation, chatbots, and other AI tools for Arabic speakers.
Hugging Face introduces QIMMA, a quality-focused leaderboard for Arabic LLMs. It aims to highlight models that excel in both performance and cultural relevance.
Researchers have developed a hybrid CNN-Transformer architecture for Arabic Speech Emotion Recognition (SER), addressing the scarcity of annotated datasets in Arabic. This model leverages convolutional layers and Transformer architecture to improve emotion detection accuracy in speech.