BUZZY: Contrastive Scoring to Mitigate Text-Induced Bias in Multimodal Multiple-Choice QA
This work hypothesizes and empirically verify that a model genuinely relies on visual evidence only when its multimodal distribution significantly diverges from its text-only distribution and proposes BUZZY, a training-free decoding method that corrects multimodal predictions by subtracting the text-only distribution.
Taeyun Roh, Suhyeong Park, Dongyoung Lee et al.
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