SUT at SemEval-2023 Task 1: Prompt Generation for Visual Word Sense Disambiguation

Omid Ghahroodi, Seyed Arshan Dalili, Sahel Mesforoush, Ehsaneddin Asgari


Abstract
Visual Word Sense Disambiguation (V-WSD) identifies the correct visual sense of a multi-sense word in a specific context. This can be challenging as images may need to provide additional context and words may have multiple senses. A proper V-WSD system can benefit applications like image retrieval and captioning. This paper proposes a Prompt Generation approach to solve this challenge. This approach improves the robustness of language-image models like CLIP to contextual ambiguities and helps them better correlate between textual and visual contexts of different senses of words.
Anthology ID:
2023.semeval-1.298
Volume:
Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023)
Month:
July
Year:
2023
Address:
Toronto, Canada
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Giovanni Da San Martino, Harish Tayyar Madabushi, Ritesh Kumar, Elisa Sartori
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
2160–2163
Language:
URL:
https://aclanthology.org/2023.semeval-1.298
DOI:
10.18653/v1/2023.semeval-1.298
Bibkey:
Cite (ACL):
Omid Ghahroodi, Seyed Arshan Dalili, Sahel Mesforoush, and Ehsaneddin Asgari. 2023. SUT at SemEval-2023 Task 1: Prompt Generation for Visual Word Sense Disambiguation. In Proceedings of the 17th International Workshop on Semantic Evaluation (SemEval-2023), pages 2160–2163, Toronto, Canada. Association for Computational Linguistics.
Cite (Informal):
SUT at SemEval-2023 Task 1: Prompt Generation for Visual Word Sense Disambiguation (Ghahroodi et al., SemEval 2023)
Copy Citation:
PDF:
https://aclanthology.org/2023.semeval-1.298.pdf