Abdalghani Abujabal — accepted AI-conference papers

2025

ALLaM: Large Language Models for Arabic and English

M Saiful Bari, Yazeed Alnumay, Norah A. Alzahrani, Nouf M. Alotaibi, Hisham Abdullah Alyahya, Sultan AlRashed +20

ICLR 2025poster

In this work, we present ALLaM: Arabic Large Language Model, a series of large language models to support the ecosystem of Arabic Language Technologies (ALT). ALLaM is carefully trained, considering the values of language alignment and transferability of knowledge at scale. The models are based on a…

Cited by 11 Source ↗PDF ↗Scholar ↗

2021

Continuous Model Improvement for Language Understanding with Machine Translation

Abdalghani Abujabal, Claudio Delli Bovi, Sungho Ryu, Turan Gojayev, Fabian Triefenbach, Yannick Versley

NAACL 2021industry

Scaling conversational personal assistants to a multitude of languages puts high demands on collecting and labelling data, a setting in which cross-lingual learning techniques can help to reconcile the need for well-performing Natural Language Understanding (NLU) with a desideratum to support many l…

Cited by 4 Source ↗PDF ↗Scholar ↗

2021

Identifying and Resolving Annotation Changes for Natural Language Understanding

Jose Garrido Ramas, Giorgio Pessot, Abdalghani Abujabal, Martin Rajman

NAACL 2021industry

Annotation conflict resolution is crucial towards building machine learning models with acceptable performance. Past work on annotation conflict resolution had assumed that data is collected at once, with a fixed set of annotators and fixed annotation guidelines. Moreover, previous work dealt with a…

Cited by 3 Source ↗PDF ↗Scholar ↗