Papers with go-to models

1 papers
Babel-ImageNet: Massively Multilingual Evaluation of Vision-and-Language Representations (2024.acl-long)

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Challenge: Vision-and-language models with separate encoders for each modality are limited in availability.
Approach: They propose a multilingual benchmark that offers (partial) translations of ImageNet labels to 100 languages, built without machine translation or manual annotation.
Outcome: The proposed model outperforms models on English and low-resource languages.

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