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Brain-inspired large model mindreading
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DOI：10.1016/j.neuroimage.2026.122108.png)
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Abstract
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• Human responses to visual ToM questions are more concise and certain. • MLLMI showed stronger bilateral precuneus and middle temporal gyrus activation. • Enhanced functional connectivity in task-coordination and attention networks in MLLMI. • Neural-based Transformer model achieved 78.6% classification accuracy. • We propose a Knowledge-Thinking-Adaptation (KTA) roadmap for AI visual ToM.
Keywords:
Multimodal large language models
Theory of mind
Visual question answering
Mentalization
Brain-inspired intelligence
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