Multilingual Vision-Language Models, A Survey

• URL: http://arxiv.org/abs/2509.22123v1
• Date: Fri, 26 Sep 2025 09:46:13 GMT
• Title: Multilingual Vision-Language Models, A Survey
• Authors: Andrei-Alexandru Manea, Jindřich Libovický,
• Abstract summary: This survey examines multilingual vision-language models that process text and images across languages.<n>We review 31 models and 21 benchmarks, spanning encoder-only and generative architectures.
• Score: 0.9722250595763385
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: This survey examines multilingual vision-language models that process text and images across languages. We review 31 models and 21 benchmarks, spanning encoder-only and generative architectures, and identify a key tension between language neutrality (consistent cross-lingual representations) and cultural awareness (adaptation to cultural contexts). Current training methods favor neutrality through contrastive learning, while cultural awareness depends on diverse data. Two-thirds of evaluation benchmarks use translation-based approaches prioritizing semantic consistency, though recent work incorporates culturally grounded content. We find discrepancies in cross-lingual capabilities and gaps between training objectives and evaluation goals.

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