A Dual-Module Denoising Approach with Curriculum Learning for Enhancing Multimodal Aspect-Based Sentiment Analysis

Nguyen Van Doan, Dat Tran Nguyen, Cam-Van Thi Nguyen


Anthology ID:
2024.paclic-1.37
Volume:
Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
Month:
December
Year:
2024
Address:
Tokyo, Japan
Editors:
Shirley Dita, Jong-Bok Kim, Ariane Borlongan, Nathaniel Oco
Venue:
PACLIC
SIG:
Publisher:
Tokyo University of Foreign Studies
Note:
Pages:
371–379
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URL:
https://preview.aclanthology.org/landing_page/2024.paclic-1.37/
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Cite (ACL):
Nguyen Van Doan, Dat Tran Nguyen, and Cam-Van Thi Nguyen. 2024. A Dual-Module Denoising Approach with Curriculum Learning for Enhancing Multimodal Aspect-Based Sentiment Analysis. In Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation, pages 371–379, Tokyo, Japan. Tokyo University of Foreign Studies.
Cite (Informal):
A Dual-Module Denoising Approach with Curriculum Learning for Enhancing Multimodal Aspect-Based Sentiment Analysis (Doan et al., PACLIC 2024)
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https://preview.aclanthology.org/landing_page/2024.paclic-1.37.pdf