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    <abstract>Idioms present a unique challenge for language models due to their non-compositional figurative interpretations, which often strongly diverge from the idiom’s literal interpretation. In this paper, we employ causal tracing to systematically analyze how pretrained causal transformers deal with this ambiguity. We localize three mechanisms: (i) Early sublayers and specific attention heads retrieve figurative interpretation, while suppressing literal interpretation. (ii) When disambiguating context precedes the idiom, the model leverages it from the earliest layer and later layers refine the interpretation if the context conflicts with the retrieved interpretation. (iii) Then, selective, competing pathways carry both interpretations: an intermediate pathway that prioritizes the figurative interpretation and a parallel direct route that favors literal interpretation, ensuring that both readings remain available. Our findings provide mechanistic evidence for idiom comprehension in autoregressive transformers.</abstract>
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%0 Conference Proceedings
%T Tug-of-war between idioms’ figurative and literal interpretations in LLMs
%A Oh, Soyoung
%A Huang, Xinting
%A Pink, Mathis
%A Hahn, Michael
%A Demberg, Vera
%Y Demberg, Vera
%Y Inui, Kentaro
%Y Marquez, Lluís
%S Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2026
%8 March
%I Association for Computational Linguistics
%C Rabat, Morocco
%@ 979-8-89176-380-7
%F oh-etal-2026-tug
%X Idioms present a unique challenge for language models due to their non-compositional figurative interpretations, which often strongly diverge from the idiom’s literal interpretation. In this paper, we employ causal tracing to systematically analyze how pretrained causal transformers deal with this ambiguity. We localize three mechanisms: (i) Early sublayers and specific attention heads retrieve figurative interpretation, while suppressing literal interpretation. (ii) When disambiguating context precedes the idiom, the model leverages it from the earliest layer and later layers refine the interpretation if the context conflicts with the retrieved interpretation. (iii) Then, selective, competing pathways carry both interpretations: an intermediate pathway that prioritizes the figurative interpretation and a parallel direct route that favors literal interpretation, ensuring that both readings remain available. Our findings provide mechanistic evidence for idiom comprehension in autoregressive transformers.
%U https://aclanthology.org/2026.eacl-long.135/
%P 2942-2958

Markdown (Informal)

[Tug-of-war between idioms’ figurative and literal interpretations in LLMs](https://aclanthology.org/2026.eacl-long.135/) (Oh et al., EACL 2026)

• Tug-of-war between idioms’ figurative and literal interpretations in LLMs (Oh et al., EACL 2026)

ACL

• Soyoung Oh, Xinting Huang, Mathis Pink, Michael Hahn, and Vera Demberg. 2026. Tug-of-war between idioms’ figurative and literal interpretations in LLMs. In Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers), pages 2942–2958, Rabat, Morocco. Association for Computational Linguistics.