Xintao Wang

Xintao Wang

Ph.D Candidate

Fudan University


Xintao Wang (王鑫涛) is a third year Ph.D candidate at Fudan University in the School of Computer Science. He is deeply fascinated with ACG (Anime, Comics & Games) culture, and is devoted to revolutionizing the ACG industry with AI techniques. Hence, his research interests primarily focus on human-like generative agents and their personas, including (but not limited to):

  1. Role-Playing Language Agents: Targeting at creating AI agents that faithfully represent specific personas, including: (1) Agents for fictional characters from books and ACG, whose applications include virtual companions, games, and content creation; and (2) Agents for real-world individuals, which deeply understand user personas to serve as their digital proxies or personal assistants.

  2. Cognitive Modeling in Language Models: Focusing on integrating anthropomorphic cognition into LLMs, such as ego-awareness, social intelligence, personalities, etc. The goal is to promote LLMs’ understanding of the inner world of themselves and others, hence enabling them to generate more cognitively-aligned and human-like responses.

  • Large Language Models
  • Autonomous Agents
  • Role-Playing Language Agents
  • ACG, J Pop, Cosplay
  • Ph.D in NLP, 2021 - 2026 (estimated)

    Fudan University

  • B.S in CS, 2017 - 2021

    Fudan University


  • May. 2024: Our InCharacter got accepted to ACL 2024, and Light Up the Shadows got accepted to ACL 2024 Findings!
  • Apr. 2024: InCharacter will be presented in the poster session in Agent Workshop @ Carnegie Mellon University!
  • Apr. 2024: The first Survey on Role-Playing Agents is out! Dive into our comprehensive survey of RPLA technologies, their applications, and the exciting potential for human-AI coexistence. Understanding role-playing paves the way for both personalized assistants and multi-agent society. Check our latest survey on role-playing agent!
  • Apr. 2024: Check out SurveyAgent! This system stands out by offering a unified platform that supports researchers through various stages of their literature review process, facilitated by a conversational interface that prioritizes user interaction and personalization! Access via homepage and have fun!
  • Mar. 2024: As a member of Takway.AI, I’m thrilled to announce that we secured the Second Prize in the InternLM Competitions, hosted by the Shanghai Artificial Intelligence Laboratory!
  • Feb. 2024: Check out InCharacter! Self-assessments on RPAs are inherently flawed - which heavily depends on LLM’s own understanding of Personality. Instead, our work revolves around interviewing characters in 14 different psychological scales, providing a more objective description of LLM’s role play abilities. Check out this project demo!


Chat-Haruhi-Suzumiya Project
Research Leader
Chat-Haruhi-Suzumiya Project
August 2023 – March 2024 Shanghai, China
Lead the research project on the personality analysis of role-playing language agents.
Knowledge Works Lab, at Fudan University
Student Research Leader
Knowledge Works Lab, at Fudan University
September 2020 – Present Shanghai, China
Responsibilities: Lead the research groups on (1) role-playing language agents and (2) knowledge-enhanced LLM applications. Memtored near 10 graduate and undergraduate students. Together, we co-authored and published multiple research papers.
FudanNLP Group, at Fudan University
Student Researcher
FudanNLP Group, at Fudan University
July 2019 – September 2020 Shanghai, China
Responsibilities: Worked on fine-tuning language models for NLP tasks.


Second Prize of the InternLM Competitions
Chinese National Scholarship
Excellent Graduates of Shanghai
Chinese National Scholarship
Huawei Scholarship
Hhctea Freshman Scholarship

Recent Publications

Quickly discover relevant content by filtering publications.
(2024). InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews. ACL 2024.

PDF Cite Code

(2024). From Persona to Personalization: A Survey on Role-Playing Language Agents. In Arxiv.

PDF Cite Project Slides

(2024). Character is Destiny: Can Large Language Models Simulate Persona-Driven Decisions in Role-Playing?. In Arxiv.

PDF Cite Project

(2024). Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works. In Arxiv.

PDF Cite Project

(2024). SurveyAgent: A Conversational System for Personalized and Efficient Research Survey. In Arxiv.

PDF Cite Code Project Slides