Beyond Cultural Knowledge: Evaluating Arabic Cultural Appropriateness of Large Language Models
Large language models (LLMs) increasingly serve users whose expectations are shaped by their cultural context, yet most cultural evaluations test what a model knows rather than how it behaves when giving open-ended recommendations, opinions, and guidance. We introduce AraBehave: 1,623 culturally grounded, open-ended Arabic prompts with 29,214 cultural-appropriateness judgments from native speakers across several Arab regions, plus a scoring model whose predictions correlate strongly with human judgments on unseen systems (Pearson r=0.74). Evaluating three Arabic-centric and three frontier LLMs, we find that cultural appropriateness is not a single capability but decomposes into two largel...
| Authors | Enes Altinisik, Hamdy Mubarak, Masoomali Fatehkia et al. |
|---|---|
| Primary category | cs.CY |
| Published | 30 July 2026 |
| Last updated at source | 30 July 2026 |
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