LLaVAC: Fine-tuning LLaVA as a Multimodal Sentiment Classifier
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arXiv
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| Hauptverfasser: | , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2025
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| _version_ | 1866915138643165184 |
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| author | Chay-intr, T. Chen, Y. Viriyayudhakorn, K. Theeramunkong, T. |
| author_facet | Chay-intr, T. Chen, Y. Viriyayudhakorn, K. Theeramunkong, T. |
| contents | We present LLaVAC, a method for constructing a classifier for multimodal sentiment analysis. This method leverages fine-tuning of the Large Language and Vision Assistant (LLaVA) to predict sentiment labels across both image and text modalities. Our approach involves designing a structured prompt that incorporates both unimodal and multimodal labels to fine-tune LLaVA, enabling it to perform sentiment classification effectively. Experiments on the MVSA-Single dataset demonstrate that LLaVAC outperforms existing methods in multimodal sentiment analysis across three data processing procedures. The implementation of LLaVAC is publicly available at https://github.com/tchayintr/llavac. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2502_02938 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | LLaVAC: Fine-tuning LLaVA as a Multimodal Sentiment Classifier Chay-intr, T. Chen, Y. Viriyayudhakorn, K. Theeramunkong, T. Computation and Language We present LLaVAC, a method for constructing a classifier for multimodal sentiment analysis. This method leverages fine-tuning of the Large Language and Vision Assistant (LLaVA) to predict sentiment labels across both image and text modalities. Our approach involves designing a structured prompt that incorporates both unimodal and multimodal labels to fine-tune LLaVA, enabling it to perform sentiment classification effectively. Experiments on the MVSA-Single dataset demonstrate that LLaVAC outperforms existing methods in multimodal sentiment analysis across three data processing procedures. The implementation of LLaVAC is publicly available at https://github.com/tchayintr/llavac. |
| title | LLaVAC: Fine-tuning LLaVA as a Multimodal Sentiment Classifier |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2502.02938 |