A Hard Nut to Crack: Idiom Detection with Conversational Large Language Models
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Abstract (arXiv)
In this work, we explore idiomatic language processing with Large Language Models (LLMs). We introduce the Idiomatic language Test Suite IdioTS, a new dataset of difficult examples specifically designed by language experts to assess the capabilities of LLMs to process figurative language at sentence level. We propose a comprehensive evaluation methodology based on an idiom detection task, where LLMs are prompted with detecting an idiomatic expression in a given English sentence. We present a thorough automatic and manual evaluation of the results and an extensive error analysis.
Key facts. Cited by 11 papers in the map (data through 14 Oct 2026). Builds on 6 of its 14 references that are in the map. First posted on arXiv 17 May 2024.
Builds on
6 of 14 references.
References · 6
- 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
- 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
- 2022FLUTE: Figurative Language Understanding through Textual Explanationscited by 79
- 2022Testing the Ability of Language Models to Interpret Figurative Languagecited by 67
- 2021AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Modelscited by 27
- 2021Investigating Robustness of Dialog Models to Popular Figurative Language Constructscited by 19
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Citing papers per year: 2024: 1; 2025: 3; 2026: 7.
11 papers.
- 2024Rolling the DICE on Idiomaticity: How LLMs Fail to Grasp Contextcited by 11
- 2025Are Large Language Models Chronically Online Surfers? A Dataset for Chinese Internet Meme Explanationcited by 6
- 2026When Meaning Isn't Literal: Exploring Idiomatic Meaning Across Languages and Modalitiescited by 4
- 2025NLP Datasets for Idiom and Figurative Language Taskscited by 2
- 2026FFE-Hallu:Hallucinations in Fixed Figurative Expressions:Benchmark of Idioms and Proverbs in the Persian Languagecited by 2
- 2026A Rising Tide Lifts All Boats: MTQE Rewards for Idioms Improve General Translation Qualitycited by 1
- 2025Evaluating Large Language Models on Multiword Expressions in Multilingual and Code-Switched Contextscited by 0
- 2026IdioLink: Retrieving Meaning Beyond Words Across Idiomatic and Literal Expressionscited by 0
- 2026Multilingual Idioms in Sentences and Conversations Across High-, Medium-, and Low-Resource Languagescited by 0
- 2026G-IdiomAlign: A Gloss-Pivoted Benchmark for Cross-Lingual Idiom Alignmentcited by 0
- 2026Easy to Complete, Hard to Choose: Investigating LLM Performance on the ProverbIT Benchmarkcited by 0
- 2026Easy to Complete, Hard to Choose: Investigating LLM Performance on the ProverbIT Benchmark5 Aug 2026
- 2026G-IdiomAlign: A Gloss-Pivoted Benchmark for Cross-Lingual Idiom Alignment17 Jun 2026
- 2026Multilingual Idioms in Sentences and Conversations Across High-, Medium-, and Low-Resource Languages1 Jun 2026
- 2026IdioLink: Retrieving Meaning Beyond Words Across Idiomatic and Literal Expressions21 May 2026
- 2026When Meaning Isn't Literal: Exploring Idiomatic Meaning Across Languages and Modalities12 Apr 2026
- 2026FFE-Hallu:Hallucinations in Fixed Figurative Expressions:Benchmark of Idioms and Proverbs in the Persian Language27 Jan 2026
- 2026A Rising Tide Lifts All Boats: MTQE Rewards for Idioms Improve General Translation Quality9 Jan 2026
- 2025NLP Datasets for Idiom and Figurative Language Tasks20 Nov 2025
- 2025Are Large Language Models Chronically Online Surfers? A Dataset for Chinese Internet Meme Explanation1 Oct 2025
- 2025Evaluating Large Language Models on Multiword Expressions in Multilingual and Code-Switched Contexts10 Apr 2025
- 2024Rolling the DICE on Idiomaticity: How LLMs Fail to Grasp Context21 Oct 2024