Zhaowei Zhang (张钊为)

Ph.D. Student
School of Intelligence Science and Technology
Peking University
Email: zwzhang [at] stu (dot) pku (dot) edu (dot) cn

[Google Scholar] [Github] [Twitter] [LinkedIn]

Research Interests
  • AI Alignment & Post-Training
  • Omni MLLM & World Models
  • Efficient AI
  • Reinforcement Learning
  • Game Theory & Mech. Design

Zhaowei is pronounced as "Ju" (as in judge) + "ou" (as in out) + "Way"; Zhang, or Cheung in Hong Kong, is "Ju" (as in judge) + "on" | audio ([International Phonetic Alphabet, IPA]) here: [tʂɑuwei][tʂɑŋ].

I am currently a third-year Ph.D. candidate at Institute for AI, School of Intelligence Science and Technology, Peking University. Specifically, I am in the team of PAIR-Lab led by Prof. Yaodong Yang. The long-term goal of my research is to build a strong and efficient AI system, which can understand, interact, and make full use of computing resources. To this end, my research focuses on Omni MLLM & World Models, Efficient ML, and Reinforcement Learning. I welcome more friends to discuss these topics with me ☺️.

Selected Publications (* indicates equal contribution.)

    2025
  • PoliCon: Evaluating LLMs on Achieving Diverse Political Consensus Objectives
    Zhaowei Zhang, Xiaobo Wang, Minghua Yi, Mengmeng Wang, Fengshuo Bai, Zilong Zheng, Yipeng Kang, Yaodong Yang
    ICLR 2026
    [Paper] [Website]
  • Evaluating Generalization Capabilities of LLM-Based Agents in Mixed-Motive Scenarios Using Concordia
    Cooperate with the DeepMind Concordia Team
    NeurIPS DB Track 2025
    [Paper]
  • Amulet: ReAlignment During Test Time for Personalized Preference Adaptation of LLMs
    Zhaowei Zhang, Fengshuo Bai, Qizhi Chen, Chengdong Ma, Mingzhi Wang, Haoran Sun, Zilong Zheng, Yaodong Yang
    ICLR 2025
    [Paper] [Website] [Code]
    • 2024
  • ValueDCG: Measuring Comprehensive Human Value Understanding Ability of Language Models
    Zhaowei Zhang, Fengshuo Bai, Jun Gao, Yaodong Yang
    NeurIPS 2025 Workshop on Regulatable ML
    [Paper] [Blog] [Chinese Blog]
  • Foundational Challenges in Assuring Alignment and Safety of Large Language Models
    As a major contributor
    TMLR
    [Paper] [Website]
  • Roadmap on Incentive Compatibility for AI Alignment and Governance in Sociotechnical Systems
    Zhaowei Zhang, Fengshuo Bai, Mingzhi Wang, Haoyang Ye, Chengdong Ma, Yaodong Yang
    AGI 2025 (Oral)
    [Paper] [Chinese Blog]
    • 2023
  • AI Alignment: A Comprehensive Survey
    PAIR-Lab
    ACM Computing Surveys
    [Paper] [Website]
  • ProAgent: Building Proactive Cooperative AI with Large Language Models
    Ceyao Zhang, Kaijie Yang, Siyi Hu, Zihao Wang, Guanghe Li, Yihang Sun, Cheng Zhang, Zhaowei Zhang, Anji Liu, Song-Chun Zhu, Xiaojun Chang, Junge Zhang, Feng Yin, Yitao Liang, Yaodong Yang
    AAAI 2024 (Oral)
    [Paper]
  • Heterogeneous Value Alignment Evaluation for Large Language Models
    Zhaowei Zhang, Nian Liu, Siyuan Qi, Ceyao Zhang, Ziqi Rong, Shuguang Cui, Song-Chun Zhu, Yaodong Yang
    AGI 2025 & AAAI 2024 Workshop: Public Sector LLMs (Oral)
    [Paper]
  • STAS: Spatial-Temporal Return Decomposition for Solving Sparse Rewards Problems in Multi-agent Reinforcement Learning
    Sirui Chen *, Zhaowei Zhang *, Yali Du, Yaodong Yang
    AAAI 2024
    [Paper] [Code]

Blogs & Tutorials

  • AI for Helping People to Find Consensus
    Abstract: This tutorial explains how to use LLMs as scalable "AI mediators" that infer preferences from large amounts of free-text opinions and generate consensus statements representing different groups, helping address information bandwidth limits, anchoring effects, and inefficiencies in real-world deliberation. It covers group-level generative social choice and stakeholder-level consensus generation and evaluation, and discusses challenges such as bias, dynamic negotiation, and interaction costs.
    [Tutorial Slides]
  • The Three-Layer Paradigm for Implementing Sociotechnical AI Alignment: A Top-Down-Top Outlook
    Abstract: This blog clarifies what socio-technical systems (STS) mean in the context of AI alignment, resolving inconsistent definitions across scales. It presents a computable, multi-scale view of STS alignment problems and outlines possible research directions.
    [English Version] [Chinese Version]

Internship

Kling AI, Kuaishou Tech.
Research Intern, working with Xintao Wang
February 2026
Microsoft Research (MSRA)
Research Intern, working with Xing Xie & Xiaoyuan Yi
September 2025 - January 2026

Selected Awards

  • Huawei Spark Award, 2025. (the only student recipient) [News]
  • [Top 5%] Wuhan University Outstanding Thesis Award, 2023.

Services

  • Reviewer for AI conferences represented by ICLR, NeurIPS, and ICML.
  • Program Committee Member for AAAI 2026 AIA Track.
  • Program Committee Member for AAAI 2026.
  • Program Committee Member for DAI 2024.