An empirical study of Multimodal Entity-Based Sentiment Analysis with ChatGPT: Improving in-context learning via entity-aware contrastive learning

Author:

Yang LiORCID,Wang ZengzhiORCID,Li ZiyanORCID,Na Jin-CheonORCID,Yu JianfeiORCID

Publisher

Elsevier BV

Reference87 articles.

1. Barnes, J., Kurtz, R., Oepen, S., Øvrelid, L., & Velldal, E. (2021). Structured Sentiment Analysis as Dependency Graph Parsing. In Proceedings of ACL-IJCNLP (pp. 3387–3402).

2. Barnes, J., Oberlaender, L., Troiano, E., Kutuzov, A., Buchmann, J., Agerri, R., et al. (2022). SemEval 2022 Task 10: Structured Sentiment Analysis. In Proceedings of the 16th international workshop on semantic evaluation (pp. 1280–1295).

3. TART: A plug-and-play Transformer module for task-agnostic reasoning;Bhatia,2023

4. Bowman, S. R., Angeli, G., Potts, C., & Manning, C. D. A large annotated corpus for learning natural language inference.

5. Language models are few-shot learners;Brown;Advances in Neural Information Processing Systems,2020

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