3 papers
cs.LG2025
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…
cs.AI2025
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…
cs.CL2025
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,…