@article{petersen-etal-2026-modelling,
title = "Modelling Analogies and Analogical Reasoning: Connecting Cognitive Science Theory and {NLP} Research",
author = "Petersen, Molly R. and
Stevenson, Claire E. and
van der Plas, Lonneke",
journal = "Transactions of the Association for Computational Linguistics",
volume = "14",
year = "2026",
address = "Cambridge, MA",
publisher = "MIT Press",
url = "https://aclanthology.org/2026.tacl-1.32/",
doi = "10.1162/tacl.a.632",
pages = "711--732",
abstract = "Analogical reasoning is an essential aspect of human cognition. In this paper, we summarize key theories about the processes underlying analogical reasoning from the cognitive science literature and relate it to current research in natural language processing. While these processes can be easily linked to concepts in NLP, they are generally not viewed through a cognitive lens. Furthermore, we show how these notions are relevant for several major challenges in NLP research, not directly related to analogy solving. This may guide researchers to better optimize relational understanding in text, as opposed to relying heavily on entity-level similarity."
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%0 Journal Article
%T Modelling Analogies and Analogical Reasoning: Connecting Cognitive Science Theory and NLP Research
%A Petersen, Molly R.
%A Stevenson, Claire E.
%A van der Plas, Lonneke
%J Transactions of the Association for Computational Linguistics
%D 2026
%V 14
%I MIT Press
%C Cambridge, MA
%F petersen-etal-2026-modelling
%X Analogical reasoning is an essential aspect of human cognition. In this paper, we summarize key theories about the processes underlying analogical reasoning from the cognitive science literature and relate it to current research in natural language processing. While these processes can be easily linked to concepts in NLP, they are generally not viewed through a cognitive lens. Furthermore, we show how these notions are relevant for several major challenges in NLP research, not directly related to analogy solving. This may guide researchers to better optimize relational understanding in text, as opposed to relying heavily on entity-level similarity.
%R 10.1162/tacl.a.632
%U https://aclanthology.org/2026.tacl-1.32/
%U https://doi.org/10.1162/tacl.a.632
%P 711-732
Markdown (Informal)
[Modelling Analogies and Analogical Reasoning: Connecting Cognitive Science Theory and NLP Research](https://aclanthology.org/2026.tacl-1.32/) (Petersen et al., TACL 2026)
ACL