AraDynFact: Dynamic Evaluation of Factual Knowledge in Arabic
As Large Language Models (LLMs) continue to scale both in size and capabilities, their proficiency in the Arabic Language has seen significant advancement. However, a critical gap remains: the extent of their factual knowledge and cultural sensitivity to the diverse Arabic-speaking world remains largely underexplored. Current evaluation metrics often focus on translation or generic reasoning, failing to capture the rich historical, social, and regional nuances inherent to Arabic culture. In addition, most benchmarks rely on heavy work, with human intervention in some steps, making the evaluation of knowledge coverage expensive and slow. To address this deficiency, we introduce AraDynFact,...
| Authors | Ignacio Iacobacci, Faroq Altam, Zhaozhi Qian et al. |
|---|---|
| Primary category | cs.CL |
| Published | 28 September 2026 |
| Last updated at source | 28 September 2026 |
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