Conversational Dynamic

Conversational dynamics research focuses on understanding and replicating the complexities of human interaction, particularly within the context of human-computer dialogue. Current research heavily utilizes large language models (LLMs) to analyze and generate conversational data, exploring applications in areas like scam detection, personalized recommendations, and social engineering defense. This work aims to improve the naturalness, effectiveness, and fairness of AI conversational agents, impacting fields ranging from cybersecurity and customer service to social science and human-computer interaction. A key challenge lies in addressing biases in training data and ensuring equitable performance across diverse user groups.