Papers by Runjia Li

1 papers
No Culture Left Behind: ArtELingo-28, a Benchmark of WikiArt with Captions in 28 Languages (2024.emnlp-main)

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Challenge: Traditionally, vision research focused on unambiguous class labels, whereas ArtELingo emphasizes diversity of opinions over languages and cultures.
Approach: They propose a vision-language benchmark that spans 28 languages and encompasses approximately 200,000 annotations.
Outcome: The proposed benchmark spans 28 languages and encompasses approximately 200,000 annotations . the challenge is to build machine learning systems that assign emotional captions to images .

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