LLMs Don't Pay for the Jump· 大模型无法完成推理跃迁
Zahavy [2026] argues that Large Language Models, despite their capabilities in induction and deduction, cannot perform the abductive "Jump" that produced Einstein's equivalence principle, and attributes this limitation to the absence of embodied simulation. Zheng-Xin [2026] and Farmer [2026] question whether embodiment is necessary for abduction, pointing to alternative routes to General Relativity and forms of abduction that require no sensorimotor grounding. Max Planck resolved the blackbody radiation problem in 1900. Planck's move to E = hν required no embodied simulation. It was motivated by a mathematical consequence of classical theory, an infinite predicted energy for a finite measured quantity, that could not be physically accepted. We show that neither induction nor deduction coul
大型语言模型无法进行与爱因斯坦等价原理类似的推理跃迁。
- 核心方法
- 分析历史上科学家如何通过非体验模拟的方式完成重要的理论突破，对比大型语言模型的能力。
- 适合谁读
- 研究者
- 要解决的问题
- 探讨大型语言模型在处理需要抽象思维和非基于体验的推理任务时的局限性。
- 关键实验
- 未提供
- 主要贡献
- 论证了大型语言模型在没有体验模拟的情况下无法完成某些类型的抽象推理。
- 意义与局限
- 该研究强调了目前大模型在理论创新和高级抽象推理方面的局限，为未来的研究方向提供了思考。