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具有重要应用价值，亦是通用人工智能（AGI）领域的核心方法论。随着基础模型的持续发展，学界对其推理能力的探索日益深入。本文系统梳理了专为推理设计或适用于推理任务的基础模型，重点阐述了各类推理任务、方法及评估基准的最新进展。在此基础上，深入探讨了基础模型推理能力涌现的潜在发展方向，并论述了多模态学习、自主智能体与超级对齐在推理研究中的关联意义。通过展望这些前沿方向，我们期望激发研究者在该领域的探索热情，推动基础模型推理能力的进一步发展，并为AGI的演进做出贡献。