Papers with massively multilingual vision-language benchmark

1 papers
MVL-SIB: A Massively Multilingual Vision-Language Benchmark for Cross-Modal Topical Matching (2025.findings-acl)

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Challenge: Existing multilingual vision-language (VL) benchmarks typically only cover a handful of languages, underscoring the need for evaluation data for low-resource languages.
Approach: They propose a multilingual vision-language benchmark that evaluates cross-modal and text-only topical matching across 205 languages.
Outcome: The proposed model performs better in cross-modal and text-only topical matching in lower-resource languages than the most multilingual benchmarks.

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