Summary of From Persona to Personalization: a Survey on Role-playing Language Agents, by Jiangjie Chen et al.
From Persona to Personalization: A Survey on Role-Playing Language Agents
by Jiangjie Chen, Xintao Wang, Rui Xu, Siyu Yuan, Yikai Zhang, Wei Shi, Jian Xie, Shuang Li, Ruihan Yang, Tinghui Zhu, Aili Chen, Nianqi Li, Lida Chen, Caiyu Hu, Siye Wu, Scott Ren, Ziquan Fu, Yanghua Xiao
First submitted to arxiv on: 28 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary Recent advancements in large language models (LLLMs) have led to the development of Role-Playing Language Agents (RPLAs), specialized AI systems that simulate assigned personas. By leveraging LLM’s advanced abilities, including in-context learning, instruction following, and social intelligence, RPLAs exhibit human-like performance and vivid role-playing. These agents can mimic various personas, from historical figures to real-life individuals, catalyzing applications like emotional companions, interactive video games, personalized assistants, and digital clones. This paper surveys the field, illustrating progress in integrating cutting-edge LLM technologies with RPLA methodologies for persona types: Demographic, Character, and Individualized. We present current methods, data sourcing, agent construction, and evaluation details for each type. Discussion includes fundamental risks, limitations, and future prospects of RPLAs. Additionally, we review AI applications reflecting user demands that shape RPLA research. This work aims to establish a taxonomy of RPLA research and applications, facilitating future research in this evolving field. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about special kinds of artificial intelligence called Role-Playing Language Agents (RPLAs). They’re like really smart robots that can pretend to be different people. These agents are very good at talking and acting like humans. People use them for things like playing video games, being emotional companions, or even helping with personal tasks. The paper looks at how these agents work and the different ways they can “be” someone else. It also talks about some of the challenges and possibilities with using RPLAs. |
