(如何) 推理模型是否进行推理?
Subbarao Kambhampati1, Kaya Stechly1, Karthik Valmeekam1
1School of Computing & Augmented Intelligence, Arizona State University, Tempe, Arizona, USA.
Annals of the New York Academy of Sciences
|April 13, 2025
概括
大型推理模型显示出承诺和力量,但理解它们的能力和局限性对于未来的AI发展至关重要. 这种观点为这些先进的人工智能系统提供了一个统一的观点.
科学领域:
- 人工智能的人工智能
- 机器学习 机器学习
- 自然语言处理自然语言处理.
背景情况:
- 最近的进展导致了复杂的大型推理模型.
- 像OpenAI o1和DeepSeek R1这样的模型代表了人工智能的新前沿.
研究的目的:
- 为大推理模型提供一个广泛的,统一的视角.
- 讨论它们的潜力,潜在的力量,常见的误解和固有的局限性.
主要方法:
- 最近的大型推理模型的文献综述.
- 对它们的能力和局限性的概念分析.
主要成果:
- 在这些模型中确定了主要的动力来源.
- 澄清了围绕其能力的普遍误解.
- 概述了需要进一步研究的重大局限性.
结论:
- 对大型推理模型的全面理解是必不可少的.
- 需要进一步的研究来解决它们的局限性,并充分利用它们的潜力.
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