@inproceedings{rasouli-etal-2025-aima,
title = "{AIMA} at {S}em{E}val-2025 Task 1: Bridging Text and Image for Idiomatic Knowledge Extraction via Mixture of Experts",
author = "Rasouli, Arash and
Sadraiye, Erfan and
Ghahroodi, Omid and
Rabiee, Hamid and
Asgari, Ehsaneddin",
editor = "Rosenthal, Sara and
Ros{\'a}, Aiala and
Ghosh, Debanjan and
Zampieri, Marcos",
booktitle = "Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)",
month = jul,
year = "2025",
address = "Vienna, Austria",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.semeval-1.296/",
pages = "2270--2275",
ISBN = "979-8-89176-273-2",
abstract = "Idioms 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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<abstract>Idioms 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.</abstract>
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%0 Conference Proceedings
%T AIMA at SemEval-2025 Task 1: Bridging Text and Image for Idiomatic Knowledge Extraction via Mixture of Experts
%A Rasouli, Arash
%A Sadraiye, Erfan
%A Ghahroodi, Omid
%A Rabiee, Hamid
%A Asgari, Ehsaneddin
%Y Rosenthal, Sara
%Y Rosá, Aiala
%Y Ghosh, Debanjan
%Y Zampieri, Marcos
%S Proceedings of the 19th International Workshop on Semantic Evaluation (SemEval-2025)
%D 2025
%8 July
%I Association for Computational Linguistics
%C Vienna, Austria
%@ 979-8-89176-273-2
%F rasouli-etal-2025-aima
%X Idioms 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.
%U https://aclanthology.org/2025.semeval-1.296/
%P 2270-2275
Markdown (Informal)
[AIMA at SemEval-2025 Task 1: Bridging Text and Image for Idiomatic Knowledge Extraction via Mixture of Experts](https://aclanthology.org/2025.semeval-1.296/) (Rasouli et al., SemEval 2025)
ACL