Multimodal Aspect-Based Sentiment Analysis under Conditional Relation

Xinjing Liu, Ruifan Li, Shuqin Ye, Guangwei Zhang, Xiaojie Wang


Abstract
Multimodal Aspect-Based Sentiment Analysis (MABSA) aims to extract aspect terms from text-image pairs and identify their sentiments. Previous methods are based on the premise that the image contains the objects referred by the aspects within the text. However, this condition cannot always be met, resulting in a suboptimal performance. In this paper, we propose COnditional Relation based Sentiment Analysis framework (CORSA). Specifically, we design a conditional relation detector (CRD) to mitigate the impact of the unmet conditional image. Moreover, we design a visual object localizer (VOL) to locate the exact condition-related visual regions associated with the aspects. With CRD and VOL, our CORSA framework takes a multi-task form. In addition, to effectively learn CORSA we conduct two types of annotations. One is the conditional relation using a pretrained referring expression comprehension model; the other is the bounding boxes of visual objects by a pretrained object detection model. Experiments on our built C-MABSA dataset show that CORSA consistently outperforms existing methods. The code and data are available at https://github.com/Liuxj-Anya/CORSA.
Anthology ID:
2025.coling-main.22
Volume:
Proceedings of the 31st International Conference on Computational Linguistics
Month:
January
Year:
2025
Address:
Abu Dhabi, UAE
Editors:
Owen Rambow, Leo Wanner, Marianna Apidianaki, Hend Al-Khalifa, Barbara Di Eugenio, Steven Schockaert
Venue:
COLING
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
313–323
Language:
URL:
https://aclanthology.org/2025.coling-main.22/
DOI:
Bibkey:
Cite (ACL):
Xinjing Liu, Ruifan Li, Shuqin Ye, Guangwei Zhang, and Xiaojie Wang. 2025. Multimodal Aspect-Based Sentiment Analysis under Conditional Relation. In Proceedings of the 31st International Conference on Computational Linguistics, pages 313–323, Abu Dhabi, UAE. Association for Computational Linguistics.
Cite (Informal):
Multimodal Aspect-Based Sentiment Analysis under Conditional Relation (Liu et al., COLING 2025)
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PDF:
https://aclanthology.org/2025.coling-main.22.pdf