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

Li Yang|Zengzhi Wang|Ziyan Li|Jin-Cheon Na|Jianfei Yu


Anthology ID:DBLP:journals/ipm/YangWLNY24
Year:2024
Venue:Information Processing and Management
Pages:103724
URL:https://doi.org/10.1016/J.IPM.2024.103724
DOI:https://doi.org/10.1016/J.IPM.2024.103724
DBLP:journals/ipm/YangWLNY24
BibTeX:
@article{yang-2024-empirical, author = {Li Yang and Zengzhi Wang and Ziyan Li and Jin-Cheon Na and Jianfei Yu}, title = {{An empirical study of Multimodal Entity-Based Sentiment Analysis with ChatGPT: Improving in-context learning via entity-aware contrastive learning}}, journal = {Information Processing and Management}, volume = {61}, number = {4}, pages = {103724}, year = {2024}, url = {https://doi.org/10.1016/J.IPM.2024.103724}, doi = {https://doi.org/10.1016/J.IPM.2024.103724} }