Enhancing Emotional Generation Capability of Large Language Models via Emotional Chain-of-Thought

arXiv:2401.06836v2 Announce Type: replace
Abstract: Large Language Models (LLMs) have shown remarkable performance in various emotion recognition tasks, thereby piquing the research community's curiosity for exploring their potential in emotional intelligence. However, several issues in the field of emotional generation tasks remain unresolved, including human preference alignment and emotional generation assessment. In this paper, we propose the Emotional Chain-of-Thought (ECoT), a plug-and-play prompting method that enhances the performance of LLMs on various emotional generation tasks by aligning with human emotional …

abstract alignment arxiv capability community cs.ai cs.cl curiosity emotion emotional intelligence human intelligence language language models large language large language models llms performance recognition research research community tasks thought type via