AI RESEARCH
Disparities In Negation Understanding Across Languages In Vision-Language Models
arXiv CS.CL
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ArXi:2604.18942v1 Announce Type: new Vision-language models (VLMs) exhibit affirmation bias: a systematic tendency to select positive captions ("X is present") even when the correct description contains negation ("no X"). While prior work has documented this failure mode in English and proposed solutions, negation manifests differently across languages through varying morphology, word order, and cliticization patterns, raising the question of whether these solutions serve all linguistic communities equitably. We.