PersonaLized Dialogue Generation

Personalized dialogue generation (PDG) aims to create conversational AI systems that produce responses tailored to individual users, going beyond generic interactions. Current research focuses on methods that learn user characteristics implicitly from dialogue history, rather than relying solely on explicitly provided persona profiles, often employing techniques like latent space modeling, retrieval augmentation, and parameter-efficient fine-tuning of large language models. This field is significant for advancing human-computer interaction, enabling more engaging and natural conversations in applications ranging from chatbots to virtual assistants.