大型语言模型中作为涌现现象的类人认知模式
Humanlike Cognitive Patterns as Emergent Phenomena in Large Language Models
AI总结：
本文系统综述了LLMs在决策偏差、推理和创造力三大认知领域的能力，发现其认知模式与人类仅部分一致，GPT-4表现出类人系统2思维，且在语言创造力上表现优异，并为人机协作及未来研究提供了指导。
摘要：
关于大型语言模型（LLMs）中涌现模式的研究在心理学和人工智能领域获得了显著关注，这促使需要提供一份综合该复杂领域的全面综述。在本文中，我们系统地回顾了LLMs在三个重要认知领域的能力：决策偏差、推理和创造力。我们利用基于成熟心理学测试的实证研究，将LLMs的表现与人类基准进行比较。在决策方面，我们的综合分析表明，尽管LLMs表现出几种类人偏差，但人类中观察到的一些偏差却不存在，这表明其认知模式仅与人类决策部分一致。在推理方面，像GPT-4这样的高级LLMs表现出类似于人类系统2思维的深思熟虑推理，而较小模型则未达到人类水平表现。在创造力方面出现了明显的二分法：虽然LLMs在讲故事等基于语言的创造性任务中表现出色，但它们在需要现实世界语境的发散性思维任务中却显得力不从心。尽管如此，研究表明LLMs作为合作者具有巨大潜力，能够在人机问题解决环境中增强创造力。在讨论关键局限性的同时，我们还为记忆、注意力和开源模型开发等领域的未来研究提供了指导。
英文摘要：
Research on emergent patterns in Large Language Models (LLMs) has gained significant traction in both psychology and artificial intelligence, motivating the need for a comprehensive review that offers a synthesis of this complex landscape. In this article, we systematically review LLMs' capabilities across three important cognitive domains: decision-making biases, reasoning, and creativity. We use empirical studies drawing on established psychological tests and compare LLMs' performance to human benchmarks. On decision-making, our synthesis reveals that while LLMs demonstrate several human-like biases, some biases observed in humans are absent, indicating cognitive patterns that only partially align with human decision-making. On reasoning, advanced LLMs like GPT-4 exhibit deliberative reasoning akin to human System-2 thinking, while smaller models fall short of human-level performance. A distinct dichotomy emerges in creativity: while LLMs excel in language-based creative tasks, such as storytelling, they struggle with divergent thinking tasks that require real-world context. Nonetheless, studies suggest that LLMs hold considerable potential as collaborators, augmenting creativity in human-machine problem-solving settings. Discussing key limitations, we also offer guidance for future research in areas such as memory, attention, and open-source model development.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
