Modal Feature Optimization Network with Prompt for Multimodal Sentiment Analysis (2025.coling-main)
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| Challenge: | Multimodal sentiment analysis(MSA) is used to understand human emotional states through multimodal. |
| Approach: | They propose a Modal Feature Optimization Network with a modal prompt attention mechanism to optimize the under-optimized modal representation by determining which modalities are under- optimized . |
| Outcome: | The proposed method outperforms existing state-of-the-art models on public benchmark datasets. |
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| Challenge: | Existing studies in Multimodal Sentiment Analysis lack a mechanism to understand complex relations between different modalities. |
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Deepanway Ghosal, Md Shad Akhtar, Dushyant Chauhan, Soujanya Poria, Asif Ekbal, Pushpak Bhattacharyya
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Self-Supervised Unimodal Label Generation Strategy Using Recalibrated Modality Representations for Multimodal Sentiment Analysis (2023.findings-eacl)
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| Challenge: | Multimodal sentiment analysis (MSA) has gained much attention over the last few years due to a lack of unimodal annotations in benchmark datasets. |
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