A new culturally inclusive and linguistically diverse dataset called Palm for Arabic LLMs is introduced, covering 22 Arab countries and featuring instructions in both Modern Standard Arabic (MSA) and dialectal Arabic (DA) across 20 topics. The dataset was built through a year-long community-driven project involving 44 researchers from across the Arab world. Evaluation of frontier LLMs using the dataset reveals limitations in cultural and dialectal understanding, with some countries being better represented than others.
Researchers introduce AceGPT, a localized large language model (LLM) specifically for Arabic, addressing cultural sensitivity and local values not well-represented in mainstream models. AceGPT incorporates further pre-training with Arabic texts, supervised fine-tuning using native Arabic instructions and GPT-4 responses, and reinforcement learning with AI feedback using a reward model attuned to local culture. Evaluations demonstrate that AceGPT achieves state-of-the-art performance among open Arabic LLMs across several benchmarks. Why it matters: This work advances culturally-aware AI development for Arabic-speaking communities, providing a valuable resource and benchmark for future research.
MBZUAI and the University of Michigan Ann Arbor have announced a new collaboration in AI research, sponsored by the U.S. Mission to the UAE. The partnership focuses on projects addressing the cultural divide in AI, with research teams from both institutions collaborating throughout the 2023/2024 academic year. A workshop titled “Bridging the Cultural Divide in AI: Analyzing Fairness, Bias, and Transparency across Cultures” will be held on April 29-30. Why it matters: The collaboration strengthens ties between the UAE and the U.S. in AI, addressing critical issues of fairness and cultural sensitivity in AI development.