Personalized Dialogue

Personalized dialogue research aims to create conversational AI systems that generate responses tailored to individual users, going beyond generic interactions. Current efforts focus on leveraging user dialogue history and limited profile information to train models, often employing techniques like parameter-efficient fine-tuning of large language models, data augmentation, and latent space modeling to overcome data scarcity and privacy concerns. This field is significant for advancing human-computer interaction, enabling more natural and engaging conversational experiences across various applications, from healthcare chatbots to personalized AI companions.