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arxiv: 2505.08910 · v2 · pith:FRVIVM4Onew · submitted 2025-05-13 · 💻 cs.CV · cs.CL

Behind Maya: Building a Multilingual Vision Language Model

classification 💻 cs.CV cs.CL
keywords languagesmultilingualmayaculturaldatasetimage-textmodelpretraining
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In recent times, we have seen a rapid development of large Vision-Language Models (VLMs). They have shown impressive results on academic benchmarks, primarily in widely spoken languages but lack performance on low-resource languages and varied cultural contexts. To address these limitations, we introduce Maya, an open-source Multilingual VLM. Our contributions are: 1) a multilingual image-text pretraining dataset in eight languages, based on the LLaVA pretraining dataset; and 2) a multilingual image-text model supporting these languages, enhancing cultural and linguistic comprehension in vision-language tasks. Code available at https://github.com/nahidalam/maya.

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    FTibSuite provides human-verified multimodal corpora, Tibetan-adapted benchmarks with quality controls, and a baseline VLM showing gains on tasks like MMBench while preserving Chinese capabilities.