Compared with standard dotted and dotless Arabic with arbitrary character remappings constrained to the same 19 undotted rasms, these findings suggest that, from an NLP perspective, Arabic character form-function relationships are largely arbitrary: models rely more on stable distributional structure than on the visual...
Dorieh M. Alomari, Irfan Ahmad, Maged Saeed Al-shaibani· 0 citations
BUL, a multi-dialect Arabic ASR dataset collected from 275 speakers in 11 Arab countries, includes structured dialect and sub-dialect coverage, as well as recordings of classical Arabic and modern standard Arabic spoken by participants in their native dialectal accents to support accent-aware modeling.
Ahmed Ashraf, Aisha Alansari, Fadel Al Abbas et al.· 1 citation
An in-depth evaluation of instruction tuning for Arabic NLP tasks using three prominent LLMs: LLaMA 3.1-8B, AceGPT-v2-8B, and Qwen3-8B shows that instruction tuning consistently improves performance across most tasks, with notable variations in effectiveness across different tasks and prompts.
Maged Saeed Al-shaibani, Zaid Alyafeai, Irfan Ahmad· Language Resources and Evalu...· 0 citations
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