Recent work (Ross et al., 2025, 2024) has argued that the ability of humans and LLMs respectively to generalize to novel adjective-noun combinations shows that they each have access to a compositional mechanism to determine the phrase's meaning and derive inferences. We study whether these inferences can instead be derived by analogy to known inferences, without need for composition. We investigate this by (1) building a model of analogical reasoning using similarity over lexical items, and (2) asking human participants to reason by analogy. While we find that this strategy works well for a large proportion of the dataset of Ross et al. (2025), there are novel combinations for which both humans and LLMs derive convergent inferences but which are not well handled by analogy. We thus conclude that the mechanism humans and LLMs use to generalize in these cases cannot be fully reduced to analogy, and likely involves composition.

翻译：近期研究（Ross等人，2025，2024）提出，人类与大型语言模型（LLMs）分别能够泛化至新颖的形容词-名词组合，这表明它们各自具备一种组合机制，用以确定短语含义并推导推断。我们探讨这些推断是否可以不通过组合，而是通过类比已知推断来推导。我们通过以下方式展开研究：（1）构建一个基于词汇项相似度的类比推理模型；（2）要求人类参与者进行类比推理。我们发现，虽然该策略在Ross等人（2025）数据集的很大一部分上表现良好，但仍存在一些新颖组合，人类与LLMs均能推导出一致的推断，而类比方法却无法妥善处理。因此我们得出结论：人类与LLMs在这些情况下进行泛化的机制不能完全简化为类比，很可能涉及组合过程。