Large multimodal models for low-resource languages: A survey

• Represents the first comprehensive analysis of LMMs specifically focused on LR languages. • Provides a novel taxonomy that categorizes existing approaches into six main categories. • Systematically organizes the literature to enable a clear understanding of current approaches and remaining challenges. • Provides an open-source repository that includes implementation details, datasets, and benchmarks. In this survey, we systematically analyze techniques used to adapt large multimodal models (LMMs) for low-resource (LR) languages, examining approaches ranging from visual enhancement and data creation to cross-modal transfer and fusion strategies. Through a comprehensive analysis of 117 studies across 96 LR…

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