mlsanityData to 7 Oct 2026

Unveiling the Secrets of Engaging Conversations: Factors that Keep Users Hooked on Role-Playing Dialog Agents

arXiv 2402.11522 ↗First posted 18 Feb 2024cs.CLcited by 7

On the map: LLM agents and tool use → Social simulation and multi-agent debate

Abstract (arXiv)

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.

Key facts. Cited by 7 papers in the map (data through 7 Oct 2026). Placed in Social simulation and multi-agent debate, one of 16 directions in LLM agents and tool use. Builds on 12 of its 20 references that are in the map. First posted on arXiv 18 Feb 2024.

Builds on

12 of 20 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024CharacterEval: A Chinese Benchmark for Role-Playing Conversational Agent Evaluation2 Jan
  2. 2023Character-LLM: A Trainable Agent for Role-Playing16 Oct
  3. 2023Generative Agents: Interactive Simulacra of Human Behavior7 Apr

Other references · 9

  1. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 13,958
  2. 2023LaMP: When Large Language Models Meet Personalizationcited by 425
  3. 2022A Contrastive Framework for Neural Text Generationcited by 224
  4. 2023Jina Embeddings 2: 8192-Token General-Purpose Text Embeddings for Long Documentscited by 103
  5. 2022Evaluating Human-Language Model Interactioncited by 90
  6. 2023A Survey on Proactive Dialogue Systems: Problems, Methods, and Prospectscited by 66
  7. 2023Rewarding Chatbots for Real-World Engagement with Millions of Userscited by 58
  8. 2023Multi-Party Chat: Conversational Agents in Group Settings with Humans and Modelscited by 53
  9. 2023Social AI Improves Well-Being Among Female Young Adultscited by 1

Built on by

Cited by year

Citing papers per year: 2024: 5; 2025: 2.

7 papers.

Similar, not cited

Close in wording, no citation either way

  1. 2026Beyond Borrowed Histories: Person-Aligned User Simulation for Interactive Role-Playing Evaluation
  2. 2025VoxRole: A Comprehensive Benchmark for Evaluating Speech-Based Role-Playing Agents
  3. 2026Role-Playing Agents Driven by Large Language Models: Current Status, Challenges, and Future Trends
  4. 2025RoleMRC: A Fine-Grained Composite Benchmark for Role-Playing and Instruction-Following
  5. 2025Enhancing User Engagement in Socially-Driven Dialogue through Interactive LLM Alignments
  6. 2025SpeechRole: A Large-Scale Dataset and Benchmark for Evaluating Speech Role-Playing Agents
  7. 2024ERABAL: Enhancing Role-Playing Agents through Boundary-Aware Learning
  8. 2023Better Zero-Shot Reasoning with Role-Play Prompting