The Landscape of Arabic Large Language Models (ALLMs): A New Era for Arabic Language Technology

TL;DR

This paper reviews the development, evaluation, and challenges of Arabic Large Language Models (ALLMs), emphasizing their potential to advance Arabic language technology and bridge digital gaps for Arabic-speaking communities.

Contribution

It provides a comprehensive overview of the evolution, benchmarking efforts, and future opportunities for ALLMs, highlighting their significance for Arabic language processing.

Findings

ALLMs have evolved from basic text systems to sophisticated models.

Benchmarking efforts are crucial for evaluating ALLMs' performance.

ALLMs can significantly impact Arabic language technology and community empowerment.

Abstract

The emergence of ChatGPT marked a transformative milestone for Artificial Intelligence (AI), showcasing the remarkable potential of Large Language Models (LLMs) to generate human-like text. This wave of innovation has revolutionized how we interact with technology, seamlessly integrating LLMs into everyday tasks such as vacation planning, email drafting, and content creation. While English-speaking users have significantly benefited from these advancements, the Arabic world faces distinct challenges in developing Arabic-specific LLMs. Arabic, one of the languages spoken most widely around the world, serves more than 422 million native speakers in 27 countries and is deeply rooted in a rich linguistic and cultural heritage. Developing Arabic LLMs (ALLMs) presents an unparalleled opportunity to bridge technological gaps and empower communities. The journey of ALLMs has been both fascinating and complex, evolving from rudimentary text processing systems to sophisticated AI-driven models. This article explores the trajectory of ALLMs, from their inception to the present day, highlighting the efforts to evaluate these models through benchmarks and public leaderboards. We also discuss the challenges and opportunities that ALLMs present for the Arab world.