Cognitive Chain-of-Thought: Structured Multimodal Reasoning about Social Situations

• URL: http://arxiv.org/abs/2507.20409v1
• Date: Sun, 27 Jul 2025 20:40:30 GMT
• Title: Cognitive Chain-of-Thought: Structured Multimodal Reasoning about Social Situations
• Authors: Eunkyu Park, Wesley Hanwen Deng, Gunhee Kim, Motahhare Eslami, Maarten Sap,
• Abstract summary: Chain-of-Thought (CoT) prompting helps models think step by step. But what happens when they must see, understand, and judge-all at once?<n>We introduce Cognitive Chain-of-Thought (CoCoT), a prompting strategy that scaffolds VLM reasoning through three cognitively inspired stages: perception, situation, and norm.
• Score: 49.16462809584473
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Chain-of-Thought (CoT) prompting helps models think step by step. But what happens when they must see, understand, and judge-all at once? In visual tasks grounded in social context, where bridging perception with norm-grounded judgments is essential, flat CoT often breaks down. We introduce Cognitive Chain-of-Thought (CoCoT), a prompting strategy that scaffolds VLM reasoning through three cognitively inspired stages: perception, situation, and norm. Our experiments show that, across multiple multimodal benchmarks (including intent disambiguation, commonsense reasoning, and safety), CoCoT consistently outperforms CoT and direct prompting (+8\% on average). Our findings demonstrate that cognitively grounded reasoning stages enhance interpretability and social awareness in VLMs, paving the way for safer and more reliable multimodal systems.

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