Using Flan-T5 for Reasoning and Extracting Emotion Causes in Conversations

The core message of this paper is to propose a two-stage Chain-of-Thought (CoT) methodology for fine-tuning large language models (LLMs) to accurately infer emotion states and causes in conversational contexts.