Is analogy enough to draw novel adjective-noun inferences?

Hayley Ross, Kathryn Davidson, Najoung Kim
3/31/2025
cs.CL

No official code found. Best implementation: rossh2/artificial-intelligence (2 stars, GPL-3.0, last commit 2025-05-19).

Abstract

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.

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Code Implementations(1)

GPL-3.0

Data for human and LLM experiments on privative adjectives, such as "Is artificial intelligence still intelligence?"

20R, PythonSep 23, 20241 years agoGPL-3.0

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Cite this paper

@article{ross2025analogy,
  title  = {Is analogy enough to draw novel adjective-noun inferences?},
  author = {Hayley Ross and Kathryn Davidson and Najoung Kim},
  year   = {2025},
  eprint = {2503.24293},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2503.24293v2}
}

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