JASMINE: Arabic GPT Models for Few-Shot Learning (2023 · 38 citations)
Research on large autoregressive language models has centred on English. Multilingual models such as BLOOM spread their capacity over many languages. Arabic is diglossic, morphologically rich, and has many dialects, some not mutually intelligible, yet it lacked sizeable dedicated decoder-only models and any benchmark…
Violet: A Vision-Language Model for Arabic Image Captioning with Gemini Decoder (2023 · 18 citations)
Arabic image captioning lags far behind English because native captioned images are scarce and strong Arabic generators have rarely been connected to vision models.
Arab Voices: Mapping Standard and Dialectal Arabic Speech Technology (2026 · 3 citations)
Speech resources for Dialectal Arabic (DA) are scattered and inconsistent. Corpora use different dialect labeling schemes (country names, broad regions, ISO codes), cover different domains, and are recorded under different conditions. This makes it hard to compare datasets or evaluate models fairly. The authors…
On the Utility of Pretraining Language Models on Synthetic Data (2024 · 3 citations)
Pretraining language models normally needs very large amounts of clean text, which low-resource languages often lack. The authors test whether Arabic models can be pretrained mostly or entirely on machine-produced text. They build four synthetic corpora:

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Updated 31 October 2026