A Context-Aware Onboarding Agent for Metaverse Powered by Large Language Models

One common asset of metaverse is that users can freely explore places and actions without linear procedures. Thus, it is hard yet important to understand the divergent challenges each user faces when onboarding metaverse. Our formative study (N = 16) shows that first-time users ask questions about metaverse that concern 1) a short-term spatiotemporal context, regarding the user’s current location, recent conversation, and actions, and 2) a long-term exploration context regarding the user’s experience history. Based on the findings, we present PICAN, a Large Language Model-based pipeline that generates context-aware answers to users when onboarding metaverse. An ablation study (N = 20) reveals that PICAN's usage of context made responses more useful and immersive than those generated without contexts. Furthermore, a user study (N = 21) shows that the use of long-term exploration context promotes users’ learning about the locations and activities within the virtual environment.