2025
ACL
ACL 2025
UCSC NLP T6 at SemEval-2025 Task 1: Leveraging LLMs and VLMs for Idiomatic Understanding
Abstract
AbstractIdiomatic expressions pose a significant challenge for natural language models due to their non-compositional nature. In this work, we address Subtask 1 of the SemEval-2025 Task 1 (ADMIRE), which requires distinguishing between idiomatic and literal usages of phrases and identify images that align with the relevant meaning.Our approach integrates large language models (LLMs) and vision-language models, and we show how different prompting techniques improve those models’ ability to identify and explain the meaning of idiomatic language.
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Interdisciplinary Bridge
— Artificial Intelligence and Machine Learning and Natural Language Processing
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Keyword Pioneer
— idiomatic expression understanding
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio