2025
ACL
ACL 2025
AIMA at SemEval-2025 Task 1: Bridging Text and Image for Idiomatic Knowledge Extraction via Mixture of Experts
Abstract
AbstractIdioms are integral components of language, playing a crucial role in understanding and processing linguistic expressions. Although extensive research has been conducted on the comprehension of idioms in the text domain, their interpretation in multi-modal spaces remains largely unexplored. In this work, we propose a multi-expert framework to investigate the transfer of idiomatic knowledge from the language to the vision modality. Through a series of experiments, we demonstrate that leveraging text-based representations of idioms can significantly enhance understanding of the visual space, bridging the gap between linguistic and visual semantics.
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Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Natural Language Processing
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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
Authors
Topics
Artificial Intelligence > Core AI > Multimodal Learning
Artificial Intelligence > Learning Paradigms > Transfer Learning
Deep Learning > Architectures > Transformers
Natural Language Processing > Resources & Methods > Multimodal NLP
Deep Learning > Learning Types > Multi-Modal Learning
Artificial Intelligence > Core AI > Multi-Modal Learning