发表机构
Birla Institute of Technology and Science, Pilani（毕拉理工与科学学院皮拉尼分校）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
该研究指出LLMs无法完成催生科学发现的溯因“跳跃”，因固定权重Transformer推理缺乏认知误差与物理代价的耦合，提出机器溯因需更深层物理机制的核心观点。
AI 中文摘要
Zahavy（2026）认为，大型语言模型（Large Language Models，LLMs）尽管具备归纳与演绎能力，却无法完成催生爱因斯坦等效原理的溯因“跳跃”，并将这一局限归因于缺少具身模拟。Zheng-Xin（2026）和Farmer（2026）质疑具身是否为溯因所必需，指出存在通向广义相对论的替代路径及无需感知运动基础的溯因形式。1900年，Max Planck解决了黑体辐射问题，他转向E = hν的过程无需具身模拟，其动机来自经典理论的数学结果——有限测量量会产生无限预测能量，这在物理上无法被接受。我们证明归纳和演绎都无法催生该公设，并主张其采用需要认知误差与物理代价的耦合。我们通过热力学耦合将这一区分形式化，表明固定权重的Transformer推理无论模型规模如何都缺乏此类耦合，这与实证结果一致：即使准确率从100%降至17%，输出熵在因果难度急剧增加的任务中仍几乎不变。因此我们认为，机器溯因中缺失的要素可能比具身更深层：系统必须具备某种物理机制，使认知误差的代价足够大以迫使其修正。
英文摘要
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 could have produced the postulate and argue that its adoption required a coupling between epistemic error and physical cost. We formalize this distinction through thermodynamic coupling and show that fixed-weight transformer inference lacks such coupling, regardless of model scale. This is consistent with empirical results showing that output entropy remains nearly unchanged across tasks with sharply increasing causal difficulty, even as accuracy falls from 100% to 17%. We therefore argue that the missing ingredient in machine abduction may lie deeper than embodiment: a system must have some physical mechanism through which epistemic error becomes costly enough to force revision.
Comments14 pages
