Reasoning is a fundamental aspect of human intelligence that plays a crucial role in activities such as problem solving, decision making, and critical thinking. In recent years, large language models (LLMs) have made significant progress in natural language processing, and there is observation that these models may exhibit reasoning abilities when they are sufficiently large. However, it is not yet clear to what extent LLMs are capable of reasoning. This paper provides a comprehensive overview of the current state of knowledge on reasoning in LLMs, including techniques for improving and eliciting reasoning in these models, methods and benchmarks for evaluating reasoning abilities, findings and implications of previous research in this field, and suggestions on future directions. Our aim is to provide a detailed and up-to-date review of this topic and stimulate meaningful discussion and future work.

翻译：推理是人类智能的基本方面，在问题解决、决策制定和批判性思维等活动中发挥着至关重要的作用。近年来，大型语言模型（LLMs）在自然语言处理领域取得了显著进展，且观察到这些模型在规模足够大时可能展现出推理能力。然而，目前尚不清楚LLMs在多大程度上具备推理能力。本文全面概述了LLMs中推理的知识现状，包括改进和激发这些模型推理能力的技术、评估推理能力的方法与基准、该领域先前研究的发现与启示，以及未来方向的建议。我们旨在提供关于该主题的详细且最新的综述，并引发有意义的讨论及未来工作。