Reasoning, a crucial ability for complex problem-solving, plays a pivotal role in various real-world settings such as negotiation, medical diagnosis, and criminal investigation. It serves as a fundamental methodology in the field of Artificial General Intelligence (AGI). With the ongoing development of foundation models, there is a growing interest in exploring their abilities in reasoning tasks. In this paper, we introduce seminal foundation models proposed or adaptable for reasoning, highlighting the latest advancements in various reasoning tasks, methods, and benchmarks. We then delve into the potential future directions behind the emergence of reasoning abilities within foundation models. We also discuss the relevance of multimodal learning, autonomous agents, and super alignment in the context of reasoning. By discussing these future research directions, we hope to inspire researchers in their exploration of this field, stimulate further advancements in reasoning with foundation models, and contribute to the development of AGI.

翻译：推理作为复杂问题求解的关键能力，在谈判、医疗诊断、刑事侦查等现实场景中发挥着核心作用，也是通用人工智能（AGI）领域的基础方法论。随着基础模型的持续发展，探索其在推理任务中的能力日益受到关注。本文系统梳理了已提出或可适配用于推理的奠基性基础模型，重点阐述各类推理任务、方法及基准测试的最新进展。进一步深入探讨基础模型推理能力涌现的潜在未来方向，并分析多模态学习、自主智能体与超级对齐在推理语境中的关联性。通过对这些未来研究方向的讨论，我们期望启发研究者在该领域的探索，推动基础模型推理能力的进一步发展，并为通用人工智能的演进做出贡献。