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

arXiv cs.CL / 4/24/2026

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Key Points

The paper frames the key deployment problem for language models in the Global South as the “last mile,” where multilingual needs and edge (resource-constrained) hardware requirements collide.
It argues that studying multilinguality and edge deployment together is necessary because linguistically diverse regions often also suffer the most severe infrastructure constraints.
The authors survey 232 papers spanning the full language-modeling pipeline, from data collection through model development to deployment.
The work outlines open research questions and offers actionable recommendations for multiple stakeholders in the NLP ecosystem to support more inclusive and equitable language technologies.
Overall, the contribution is a state-of-the-art and challenge-focused synthesis aimed at bridging gaps between otherwise siloed edge and multilingual NLP research communities.

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.