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Mind What Matters for Reasoning: Aligning Cross-Modal Attention via Selective Probability Mass Concentration
Multimodal large language models (MLLMs) achieve strong performance on visual reasoning tasks, yet remain prone to hallucinations and over-reliance on language priors, often generating answers without adequately using task-relevant visual evidence. Existing approaches primarily improve reasoning thr
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