Leveraging Large Language Models to Efficiently Collect Personalized Multi-Session Conversational Data

The authors propose LAPS, an LLM-Augmented Personalized Self-Dialogue method, to efficiently collect large-scale, human-written, multi-session, and multi-domain conversational data with extracted user preferences.