InsideOut: Unifying Emotional LLMs to Foster Empathy

Abstract

This paper introduces InsideOut, an original innovative framework that augments the emotional intelligence of Large Language Models (LLMs). Motivated by the cartoon, InsideOut is designed around a net of specialized agents, each dedicated to one of Ekman’s fundamental emotions. These agents collaboratively refine responses sensitive to the emotional context of interactions. Our assessments, conducted using EmpatheticDialogues and involving models like GPT-4 and GigaChat, indicate substantial improvements in identifying human emotions and generating empathetic responses. These improvements are most evident in situations with apparent valence-arousal differences. InsideOut offers a promising avenue for evolving AI into more perceptive and human-centric communicators.