2 citations · 5 across the 5 of their papers we have counts for
5 papers
Fine-Grained Emotion Recognition via In-Context Learning
Zhaochun Ren, Zhou Yang, Chenglong Ye +4
Fine-grained emotion recognition aims to identify the emotional type in queries through reasoning and decision-making processes, playing a crucial role in various systems. Recent m…
Exploring Information Processing in Large Language Models: Insights from Information Bottleneck Theory
Zhou Yang, Zhengyu Qi, Zhaochun Ren +4
Large Language Models (LLMs) have demonstrated remarkable performance across a wide range of tasks by understanding input information and predicting corresponding outputs. However,…
E-ICL: Enhancing Fine-Grained Emotion Recognition through the Lens of Prototype Theory
Zhaochun Ren, Zhou Yang, Chenglong Ye +6
In-context learning (ICL) achieves remarkable performance in various domains such as knowledge acquisition, commonsense reasoning, and semantic understanding. However, its performa…
Enhancing Empathetic Response Generation by Augmenting LLMs with Small-scale Empathetic Models
Zhou Yang, Zhaochun Ren, Wang Yufeng +4
Empathetic response generation is increasingly significant in AI, necessitating nuanced emotional and cognitive understanding coupled with articulate response expression. Current l…
An Iterative Associative Memory Model for Empathetic Response Generation
Zhou Yang, Zhaochun Ren, Yufeng Wang +4
Empathetic response generation aims to comprehend the cognitive and emotional states in dialogue utterances and generate proper responses. Psychological theories posit that compreh…