AladdinFTI, the proposed system is designed to both generate and translate dialectal Arabic (DA), and supports text generation in Moroccan, Egyptian, Palestinian, Syrian, and Saudi dialects, as well as bidirectional translation between these dialects, Modern Standard Arabic, and English.
A bidirectional Mamba encoder pretrained via masked language modeling on a corpus combining Arabic Wikipedia and CulturaX text is introduced, trained end-to-end on four consumer-grade NVIDIA RTX 2080Ti GPUs (11GB) over approximately ten days.
YallaMorph is introduced, a large-scale benchmark for Arabic morphological generation covering verbs, nouns, adjectives, their cliticized forms, and invalid configurations over 600K benchmark entries, which shows that Arabic morphological generation remains difficult.
Mahmoud Reda, Salam Khalifa, Reham M. Marzouk et al.· 0 citations
This paper describes the Rosetta system for Subtask 1 (Context-Aware English-to-Dialectal Arabic Dialogue Translation) of the AlexandriaX shared task, participating in both constrained and unconstrained tracks. The approach fine-tunes a LoRA adapter on NileChat-3B using structured system/user prompts that condition gen...
N. Esmaeil, Fathima Rena, S. Subhash et al.· 1 citation
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
ArabCulture-Dialogue is introduced, a culturally grounded conversational dataset covering 13 Arabic-speaking countries, in both MSA and each country’s respective dialect, spanning 12 daily-life topics and 54 fine-grained subtopics, to address the performance gap between MSA and Arabic dialects.
M. Dehan, Aldry Kautsar, SaeedAlmheiri et al.· 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
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