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This paper surveys 232 works at the intersection of multilingual language models and edge deployment, highlighting the challenges and opportunities for deploying LMs in resource-constrained, non-English-speaking communities in the Global South. It identifies key bottlenecks across the LM pipeline, from data collection to deployment, where multilinguality and edge computing requirements compete. The authors provide actionable recommendations for researchers and practitioners to foster more inclusive and equitable language technologies.
Deploying language models in the Global South requires bridging the gap between multilingual NLP and edge computing, two fields that have largely evolved independently despite their shared goals.
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.
