AINeutralarXiv – CS AI · Jun 26/10
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Understanding the Effects of Distractors on Reasoning Vision-Language Models
Researchers investigate how irrelevant visual information affects reasoning in vision-language models, finding that visual distractors reduce accuracy without lengthening reasoning traces—contrasting with textual distractors in language models. The study introduces a new dataset and proposes a prompting strategy to mitigate distractor-driven errors in multimodal AI systems.