mlsanityData to 14 Oct 2026

A Hard Nut to Crack: Idiom Detection with Conversational Large Language Models

arXiv 2405.10579 ↗First posted 17 May 2024cs.CLcited by 11

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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

  1. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 13,028
  2. 2023Judging LLM-as-a-Judge with MT-Bench and Chatbot Arenacited by 8,626
  3. 2022FLUTE: Figurative Language Understanding through Textual Explanationscited by 79
  4. 2022Testing the Ability of Language Models to Interpret Figurative Languagecited by 67
  5. 2021AStitchInLanguageModels: Dataset and Methods for the Exploration of Idiomaticity in Pre-Trained Language Modelscited by 27
  6. 2021Investigating Robustness of Dialog Models to Popular Figurative Language Constructscited by 19

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 3; 2026: 7.

11 papers.