Underlying Emotion

Underlying emotion research aims to understand how emotions are expressed, perceived, and processed, particularly within the context of human communication and interaction. Current research heavily utilizes large language models (LLMs) and other deep learning architectures like transformers and convolutional neural networks to analyze textual, visual, and auditory data for emotion detection, classification, and generation, often incorporating multimodal information and psychological theories. This work is significant for advancing our understanding of human emotion and has implications for improving human-computer interaction, personalized education, mental health applications, and the development of more ethical and nuanced AI systems.