← Back to Model Beat
Research·12h ago·all news from October 21, 2026

Benchmarking Arabic Dialects for Math Problems

arXiv:2610.28607v1 Announce Type: new Abstract: Mathematical reasoning remains underexplored for low-resource languages, including Dialectal Arabic. To bridge this gap, we introduce the DAR-MGSM (Dialectal Arabic Multilingual Grade School Math) Benchmark, the first manually curated benchmark for evaluating mathematical reasoning in Dialectal Arabic. DAR-MGSM consists of math word problems (MWPs) requiring multi-step reasoning and covers five major Arabic dialects alongside Modern Standard Arabic (MSA). The benchmark comprises two parallel versions: translated-only and translated & culturally localized. The latter version adapts entities and references to regional varieties. We evaluate eleven Arabic-centric and multilingual large language models on DAR-MGSM. The results show that the performance generally declines on the localized version, highlighting the challenges introduced by culturally grounded adaptations. However, the magnitude of this effect varies across models, with Arabic-centric models exhibiting different levels of sensitivity to localization. A mechanistic interpretability analysis shows that translated and localized variants of the same MWPs often…

Covered by 1 source

  • AarXiv CS.AI↗Noor Abo Mokh, Teresa Lynn, Nizar Habash, Ahmed Elshabrawy, Sara Alhajeri, Alaa Elsetohy, Preslav Nakov, Alham Fikri Aji12h ago

Related stories

ResearchUsing thousands of AI agents to uncover new leads in biological dataOct 21 · 2 sourcesResearchAI agents chasing a $465 train refund invented excuses, leaked medical data, and spammed an MP's officeOct 18 · 2 sourcesResearchWorld Models with Configurable PerceptionOct 21ResearchNeural Operator Splitting for Fluid Dynamics in Complex GeometryOct 21