Related papers: Tug-of-war between idiom's figurative and literal meanings in LLMs

Tug-of-war between idiom's figurative and literal meanings in LLMs

URL: http://arxiv.org/abs/2506.01723v3
Date: Fri, 06 Jun 2025 13:41:57 GMT
Title: Tug-of-war between idiom's figurative and literal meanings in LLMs
Authors: Soyoung Oh, Xinting Huang, Mathis Pink, Michael Hahn, Vera Demberg,
Abstract summary: Non-compositional figurative meanings often strongly diverge from the idiom's literal interpretation.<n>This duality requires a model to learn representing and deciding between the two meanings to interpret an idiom in a figurative sense, or literally.<n>We use tools from mechanistic interpretability to trace how a large pretrained causal transformer deals with this ambiguity.
Score: 16.986454464806616
License: http://creativecommons.org/licenses/by/4.0/
Abstract: Idioms present a unique challenge for language models due to their non-compositional figurative meanings, which often strongly diverge from the idiom's literal interpretation. This duality requires a model to learn representing and deciding between the two meanings to interpret an idiom in a figurative sense, or literally. In this paper, we employ tools from mechanistic interpretability to trace how a large pretrained causal transformer (LLama3.2-1B-base) deals with this ambiguity. We localize three steps of idiom processing: First, the idiom's figurative meaning is retrieved in early attention and MLP sublayers. We identify specific attention heads which boost the figurative meaning of the idiom while suppressing the idiom's literal interpretation. The model subsequently represents the figurative representation through an intermediate path. Meanwhile, a parallel bypass route forwards literal interpretation, ensuring that a both reading remain available. Overall, our findings provide a mechanistic evidence for idiom comprehension in an autoregressive transformer.

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