This work explores the potential of in-context learning (ICL) with a representative large language model, ChatGPT, for the MEBSA task.

This work explores the potential of in-context learning (ICL) with a representative large language model, ChatGPT, for the MEBSA task.

Jul 3, 2024 · An empirical study of Multimodal Entity-Based Sentiment Analysis with ChatGPT: Improving in-context learning via entity-aware contrastive ...

Experiments demonstrate that our developed ICL framework exhibits superior performance over other baseline ICL methods, and is comparable to or even outperforms ...

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

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

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

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

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

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