Model Card for unige-fti/Aladdin-3B

Multidialectal Arabic generation and translation model fine-tuned for dialect fidelity and diglossia.

Model Details

Model Description

Base model: SmolLM3-3B
Architecture: Decoder-only causal transformer (SmolLM architecture)
Parameters: ~3B
Language coverage: Arabic dialects, Modern Standard Arabic (MSA), English

Primary tasks:

Dialectal Arabic generation
Bidirectional translation (DA ↔ MSA ↔ English)
Controlled generation conditioned on dialect instructions

This model was fine-tuned by the Aladdin-FTI team for the AMIYA shared task to jointly optimize:

Machine translation (semantic adequacy & diglossia)

Instruction-formatted prompts:

Translate from English into Egyptian Arabic:
<SOURCE>

Instruction-conditioned generation (dialect fidelity)

Complete the sentence in Moroccan Arabic:
<PREFIX>

The objective balances meaning preservation and dialect naturalness in Arabic diglossia settings.

Model Sources

Repository: Github repository
Paper: https://arxiv.org/abs/2602.16290

How to Get Started with the Model

TODO

Training Details

Training Data: Closed-track training data only.

Datasets span multiple dialect regions and domains

Parallel corpora:

SauDial
Casablanca corpus
JODA
UFAL Levantine
DODA
Atlas

Monolingual dialect corpora:

MADAR
Shami
Saudi Tweets
EDGAD / EDC
HABIBI lyrics

Citation

If you use this model in your research, please cite the following paper:

@inproceedings{mutal2026aladdinfti,
  title     = {Aladdin-FTI @ AMIYA: Three Wishes for Arabic NLP: Fidelity, Diglossia, and Multidialectal Generation},
  author    = {Mutal, Jonathan and Al Almaoui, Perla and Hengchen, Simon and Bouillon, Pierrette},
  booktitle = {Proceedings of the AMIYA Shared Task, co-located with VarDial at EACL 2026},
  year      = {2026},
  address   = {Rabat, Morocco},
  publisher = {Association for Computational Linguistics},
}