VLMs exhibit affirmation bias that varies by language, with a new multilingual benchmark showing CLIP at or below chance on non-Latin scripts, MultiCLIP most uniform, and SpaceVLM corrections effective unevenly across typologies.
arXiv preprint arXiv:2307.13405 , year=
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Disparities In Negation Understanding Across Languages In Vision-Language Models
VLMs exhibit affirmation bias that varies by language, with a new multilingual benchmark showing CLIP at or below chance on non-Latin scripts, MultiCLIP most uniform, and SpaceVLM corrections effective unevenly across typologies.
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