7 papers
HER: Human-like Reasoning and Reinforcement Learning for LLM Role-playing
Chengyu Du, Xintao Wang, Aili Chen +11
LLM role-playing, i.e., using LLMs to simulate specific personas, has emerged as a key capability in various applications, such as companionship, content creation and digital games…
CoSER: A Comprehensive Literary Dataset and Framework for Training and Evaluating LLM Role-Playing and Persona Simulation
Xintao Wang, Heng Wang, Yifei Zhang +9
Role-playing language agents (RPLAs) have emerged as promising applications of large language models (LLMs). However, simulating established characters presents a challenging task…
Curse of Knowledge: When Complex Evaluation Context Benefits yet Biases LLM Judges
Weiyuan Li, Xintao Wang, Siyu Yuan +5
As large language models (LLMs) grow more capable, they face increasingly diverse and complex tasks, making reliable evaluation challenging. The paradigm of LLMs as judges has emer…
Capturing Minds, Not Just Words: Enhancing Role-Playing Language Models with Personality-Indicative Data
Yiting Ran, Xintao Wang, Rui Xu +4
Role-playing agents (RPA) have been a popular application area for large language models (LLMs), attracting significant interest from both industry and academia.While existing RPAs…
MINDECHO: Role-Playing Language Agents for Key Opinion Leaders
Rui Xu, Dakuan Lu, Xiaoyu Tan +5
Large language models~(LLMs) have demonstrated impressive performance in various applications, among which role-playing language agents (RPLAs) have engaged a broad user base. Now,…
From Persona to Personalization: A Survey on Role-Playing Language Agents
Jiangjie Chen, Xintao Wang, Rui Xu +15
Recent advancements in large language models (LLMs) have significantly boosted the rise of Role-Playing Language Agents (RPLAs), i.e., specialized AI systems designed to simulate a…