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Author

Teresa Lynn

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#artificial intelligence Preprint Oct 2026

Benchmarking Arabic Dialects for Math Problems

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 consist...

Noor Abo Mokh, Teresa Lynn, N. Habash et al. · 0 citations
#artificial intelligence Preprint Sep 2026

EDRAC: Benchmarking Arabic Dialect Reading Comprehension

This work introduces EDRAC, the first large-scale benchmark for dialectal Arabic machine reading comprehension (MRC) and generative QA, covering five major dialects: Egyptian, Moroccan, Emirati, Syrian, and Saudi Arabic, and benchmarks Arabic-centric and multilingual LLMs on EDRAC using lexical and semantic metrics.

Noor Abo Mokh, K. Chirkunov, Teresa Lynn et al. · 0 citations

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