Papers with Multimodal aspect-based sentiment analysis
Dual-Encoder Transformers with Cross-modal Alignment for Multimodal Aspect-based Sentiment Analysis (2022.aacl-main)
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| Challenge: | Multimodal aspect-based sentiment analysis (MABSA) aims to extract aspect terms from text and image pairs, and then analyze their corresponding sentiment. |
| Approach: | They propose a dual-encoder transformer with cross-modal alignment to extract aspect terms from text and image pairs and then analyze their corresponding sentiments. |
| Outcome: | The proposed approach outperforms existing methods on two benchmarks. |
AoM: Detecting Aspect-oriented Information for Multimodal Aspect-Based Sentiment Analysis (2023.findings-acl)
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| Challenge: | Existing methods to extract aspects from text-image pairs and recognize their sentiments are noisy and coarsely establishing image-aspect alignment will interfere with aspect-relevant semantic and sentiment information. |
| Approach: | They propose an Aspect-oriented method to detect aspect-relevant semantic and sentiment information by selecting textual tokens and image blocks that are semantically related to the aspects. |
| Outcome: | The proposed method is superior to existing methods in the field of sentiment analysis. |