Weize Liu

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I am a first-year Ph.D. student in Computer Science at the University of Maryland, College Park, advised by Prof. Furong Huang.

My research interests lie in improving foundation models, particularly Large Language Models (LLMs), with a focus on reasoning, agentic capabilities, synthetic data, and reinforcement learning. My previous research experience has primarily focused on enhancing the reasoning, reliability, interpretability, and efficiency of LLMs through post-training (SFT, RL) and data synthesis techniques. I am currently continuing my work to improve the reasoning and agentic capabilities of LLMs by developing better algorithms and data.

I am actively seeking a research internship for summer 2026 (based in the United States) and welcome any referrals or connections. I am also open to research collaborations; if you are interested in working together, please feel free to reach out via email.

news

Sep 2025 Started the Computer Science Ph.D. program at the University of Maryland, College Park.
Jun 2025 Completed the M.Eng. in Computer Technology at Zhejiang University.
May 2025 Started a research internship at Alibaba Group, enhancing the reasoning capabilities of Qwen3 models through data synthesis techniques.

selected publications

  1. arXiv
    DESIGNER: Design-Logic-Guided Multidisciplinary Data Synthesis for LLM Reasoning
    Weize Liu, Yongchi Zhao, Yijia Luo, and 8 more authors
    arXiv preprint 2025
  2. NAACL
    Mind’s Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models
    Weize Liu, Guocong Li, Kai Zhang, and 6 more authors
    NAACL 2024
  3. EMNLP
    Unraveling Babel: Exploring Multilingual Activation Patterns of LLMs and Their Applications
    Weize Liu, Yinlong Xu, Hongxia Xu, and 3 more authors
    EMNLP 2024
  4. ACL
    From Misleading Queries to Accurate Answers: A Three-Stage Fine-Tuning Method for LLMs
    Guocong Li, Weize Liu, Yihang Wu, and 4 more authors
    ACL 2025