Emotional Intelligence
Emotional intelligence (EI) research focuses on understanding and modeling the ability to perceive, understand, manage, and utilize emotions, both in humans and increasingly, in artificial intelligence. Current research emphasizes developing and evaluating AI models, particularly large language models (LLMs), for EI capabilities using benchmarks that assess emotion recognition, understanding, and regulation, often employing techniques like deep learning and natural language processing. This work has implications for improving human-computer interaction, personalized healthcare, and educational tools, as well as advancing our fundamental understanding of both human and artificial intelligence.
Papers
IMBUE: Improving Interpersonal Effectiveness through Simulation and Just-in-time Feedback with Human-Language Model Interaction
Inna Wanyin Lin, Ashish Sharma, Christopher Michael Rytting, Adam S. Miner, Jina Suh, Tim Althoff
EmoBench: Evaluating the Emotional Intelligence of Large Language Models
Sahand Sabour, Siyang Liu, Zheyuan Zhang, June M. Liu, Jinfeng Zhou, Alvionna S. Sunaryo, Juanzi Li, Tatia M. C. Lee, Rada Mihalcea, Minlie Huang