2024/02/18 by Shuai Zhang, Yu Lu, Zhang, Shuai +11 · 1 citation
Computer Science · #AI in Service Interactions #Computation and Language (cs.CL) #FOS: Computer and information sciences #Speech and dialogue systems
paper · pdf · doi:10.48550/arxiv.2402.11522
openalex publication_date 2024/02/18 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
With the growing humanlike nature of dialog agents, people are now engaging in extended conversations that can stretch from brief moments to substantial periods of time. Understanding the factors that contribute to sustaining these interactions is crucial, yet existing studies primarily focusing on short-term simulations that rarely explore such prolonged and real conversations. In this paper, we investigate the factors influencing retention rates in real interactions with roleplaying models. By analyzing a large dataset of interactions between real users and thousands of characters, we systematically examine multiple factors and assess their impact on user retention rate. Surprisingly, we find that the degree to which the bot embodies the roles it plays has limited influence on retention rates, while the length of each turn it speaks significantly affects retention rates. This study sheds light on the critical aspects of user engagement with role-playing models and provides valuable insights for future improvements in the development of large language models for role-playing purposes.