大型语言模型的动机机制

摘要

动机是驱动人类行为的核心要素，它塑造着决策、目标和任务表现。随着大语言模型与人类偏好日益对齐，我们探究其是否展现出类似动机的特征。通过研究大语言模型是否"呈现"不同水平的动机、这些呈现如何关联其行为，以及外部因素能否对其产生影响，实验结果显示出一致且结构化的模式——这些模式与人类心理学遥相呼应：自我报告的动机水平与不同行为特征相契合，随任务类型变化，并能被外部干预调节。这些发现表明，动机是组织大语言模型行为的一贯性建构，系统性地联结了行为报告、任务选择、投入程度和表现水平，展现出与人类心理学记载相似的动机动态机制。该视角深化了我们对模型行为及其与人类启发式概念关联的理解。

English

Motivation is a central driver of human behavior, shaping decisions, goals, and task performance. As large language models (LLMs) become increasingly aligned with human preferences, we ask whether they exhibit something akin to motivation. We examine whether LLMs "report" varying levels of motivation, how these reports relate to their behavior, and whether external factors can influence them. Our experiments reveal consistent and structured patterns that echo human psychology: self-reported motivation aligns with different behavioral signatures, varies across task types, and can be modulated by external manipulations. These findings demonstrate that motivation is a coherent organizing construct for LLM behavior, systematically linking reports, choices, effort, and performance, and revealing motivational dynamics that resemble those documented in human psychology. This perspective deepens our understanding of model behavior and its connection to human-inspired concepts.

大型语言模型的动机机制

Motivation in Large Language Models

摘要

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