Multilinguality at the Edge: Developing Language Models for the Global South

TL;DR

This paper surveys the challenges and opportunities of deploying multilingual language models at the edge in the Global South, emphasizing inclusivity and technical constraints.

Contribution

It provides a comprehensive survey of 232 papers on multilingual edge deployment, highlighting challenges and offering actionable recommendations.

Findings

Multilingual edge deployment faces significant infrastructural challenges.

Current research remains siloed between multilingual NLP and edge computing.

The survey identifies key open questions and future directions.

Abstract

Where and how language models (LMs) are deployed determines who can benefit from them. However, there are several challenges that prevent effective deployment of LMs in non-English-speaking and hardware constrained communities in the Global South. We call this challenge the last mile: the intersection of multilinguality and edge deployment, where the goals are aligned but the technical requirements often compete. Studying these two fields together is both a need, as linguistically diverse communities often face the most severe infrastructure constraints, and an opportunity, as edge and multilingual NLP research remain largely siloed. To understand the state of the art and the challenges of combining the two areas, we survey 232 papers that tackle this problem across the language modelling pipeline, from data collection to development and deployment. We also discuss open questions and provide actionable recommendations for different stakeholders in the NLP ecosystem. Finally, we hope that this work contributes to the development of inclusive and equitable language technologies.