@inproceedings{mutal-etal-2026-aladdin,
title = "Aladdin-{FTI} @ {AMIYA} Three Wishes for {A}rabic {NLP}: Fidelity, Diglossia, and Multidialectal Generation",
author = "Mutal, Jonathan and
Al Almaoui, Perla and
Hengchen, Simon and
Bouillon, Pierrette",
booktitle = "Proceedings of the 13th Workshop on {NLP} for Similar Languages, Varieties and Dialects",
month = mar,
year = "2026",
address = "Rabat, Morocco",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2026.vardial-1.27/",
pages = "339--351",
abstract = "Arabic dialects have long been under-represented in Natural Language Processing (NLP) research due to their non-standardization and high variability, which pose challenges for computational modeling. Recent advances in the field, such as Large Language Models (LLMs), offer promising avenues to address this gap by enabling Arabic to be modeled as a pluricentric language rather than a monolithic system. This paper presents Aladdin-FTI, our submission to the AMIYA shared task. The proposed system is designed to both generate and translate dialectal Arabic (DA). Specifically, the model supports text generation in Moroccan, Egyptian, Palestinian, Syrian, and Saudi dialects, as well as bidirectional translation between these dialects, Modern Standard Arabic (MSA), and English. The code and trained model will be released upon paper acceptance."
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%0 Conference Proceedings
%T Aladdin-FTI @ AMIYA Three Wishes for Arabic NLP: Fidelity, Diglossia, and Multidialectal Generation
%A Mutal, Jonathan
%A Al Almaoui, Perla
%A Hengchen, Simon
%A Bouillon, Pierrette
%S Proceedings of the 13th Workshop on NLP for Similar Languages, Varieties and Dialects
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%F mutal-etal-2026-aladdin
%X Arabic dialects have long been under-represented in Natural Language Processing (NLP) research due to their non-standardization and high variability, which pose challenges for computational modeling. Recent advances in the field, such as Large Language Models (LLMs), offer promising avenues to address this gap by enabling Arabic to be modeled as a pluricentric language rather than a monolithic system. This paper presents Aladdin-FTI, our submission to the AMIYA shared task. The proposed system is designed to both generate and translate dialectal Arabic (DA). Specifically, the model supports text generation in Moroccan, Egyptian, Palestinian, Syrian, and Saudi dialects, as well as bidirectional translation between these dialects, Modern Standard Arabic (MSA), and English. The code and trained model will be released upon paper acceptance.
%U https://aclanthology.org/2026.vardial-1.27/
%P 339-351
Markdown (Informal)
[Aladdin-FTI @ AMIYA Three Wishes for Arabic NLP: Fidelity, Diglossia, and Multidialectal Generation](https://aclanthology.org/2026.vardial-1.27/) (Mutal et al., VarDial 2026)
ACL