The Mind in the Machine: A Survey of Incorporating Psychological Theories in LLMs

• URL: http://arxiv.org/abs/2505.00003v1
• Date: Fri, 28 Mar 2025 16:55:24 GMT
• Title: The Mind in the Machine: A Survey of Incorporating Psychological Theories in LLMs
• Authors: Zizhou Liu, Ziwei Gong, Lin Ai, Zheng Hui, Run Chen, Colin Wayne Leach, Michelle R. Greene, Julia Hirschberg,
• Abstract summary: This paper reviews how psychological theories can inform and enhance stages of Large Language Models (LLMs) development.<n>Our survey integrates insights from cognitive, developmental, behavioral, social, personality psychology, and psycholinguistics.<n>By examining both cross-domain connections and points of tension, we aim to bridge disciplinary divides and promote more thoughtful integration of psychology into future NLP research.
• Score: 5.4397630776007615
• License: http://creativecommons.org/licenses/by-nc-sa/4.0/
• Abstract: Psychological insights have long shaped pivotal NLP breakthroughs, including the cognitive underpinnings of attention mechanisms, formative reinforcement learning, and Theory of Mind-inspired social modeling. As Large Language Models (LLMs) continue to grow in scale and complexity, there is a rising consensus that psychology is essential for capturing human-like cognition, behavior, and interaction. This paper reviews how psychological theories can inform and enhance stages of LLM development, including data, pre-training, post-training, and evaluation\&application. Our survey integrates insights from cognitive, developmental, behavioral, social, personality psychology, and psycholinguistics. Our analysis highlights current trends and gaps in how psychological theories are applied. By examining both cross-domain connections and points of tension, we aim to bridge disciplinary divides and promote more thoughtful integration of psychology into future NLP research.

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