Shenzhi Wang

Shenzhi Wang

PhD Candidate of Artificial Intelligence

Tsinghua University


I’m Shenzhi Wang (王慎执 in Chinese), a third-year Ph.D. student at LEAP Lab in the Department of Automation at Tsinghua University, advised by Prof. Shiji Song and Prof. Gao Huang. Before that, I received my B.E. degree (with honors) at SHENYUAN Honors College of Beihang University, majoring in Computer Science and Technology.

In my spare time, I write some Chinese tech blogs on Zhihu (知乎) and have 5k+ followers. Welcome to follow my Zhihu account!

Important: I am actively looking for a visiting student position for the Fall 2024 semester. If you have any available positions, I would be very interested. Please feel free to contact me via!

  • Reinforcement Learning
  • LLM-as-Agent
  • Computer Vision
  • PhD Student in Artificial Intelligence, 2021 - Present

    Department of Automation, Tsinghua University

  • B.Eng. in Computer Science and Technology, 2017 - 2021

    SHENYUAN Honors College, Beihang University


  • Oct 20, 2023 Honered to receive the First-Class Comprehensive Scholarship for Graduate Students from Tsinghua University in 2023.
  • Oct 02, 2023 We have released a preprint paper about LLMs dealing with deceptions in the Avalon game; see this Arxiv link.
  • Sep 22, 2023 One paper is accepted by NeurIPS 2023 as Spotlight; see this Arxiv link.
  • Jul 03, 2023 One paper is accepted by IEEE TNNLS!
  • Apr 23, 2023 One paper is accepted by ICML 2023!
  • Mar 01, 2021 One paper is accepted to CVPR 2021!
  • Dec 09, 2020 Honored to be one of 21 undergraduates awarded SenseTime Scholarship, 2020.


    Quickly discover relevant content by filtering publications.
    (2023). Avalon's Game of Thoughts: Battle Against Deception through Recursive Contemplation. Arxiv preprint.

    Arxiv Website 机器之心报道 新智元报道 量子位报道

    (2023). Train Once, Get a Family: State-Adaptive Balances for Offline-to-Online Reinforcement Learning. In NeurIPS (Spotlight).

    Cite Arxiv Website Code

    (2023). Hundreds Guide Millions: Adaptive Offline Reinforcement Learning with Expert Guidance. IEEE TNNLS.

    Cite Arxiv

    (2023). Boosting Offline Reinforcement Learning with Action Preference Query. In ICML.

    Cite Arxiv

    (2021). Glancing at the Patch: Anomaly Localization with Global and Local Feature Comparison. In CVPR.

    Cite Paper

    Academic Services

    Reviewer for Conferences: NeurIPS, ICLR, and ICRA;

    Reviewer for Journal: RA-L;

    Reviewer for Workshop: ICLR 2024 AGI Workshop.


      For more information about my work or to learn more about me, please don’t hesitate to reach out via email or in person.

      • (preferred),
      • 616 Center Main Building, Tsinghua University, Beijing 100084, China.