Zhongyang Li

li.17258@osu.edu

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Hi! I am a first-year CS PhD student at Ohio State University, advised by Prof. Huan Sun and working with OSU NLP. Previously, I was a Master’s student at Johns Hopkins University, advised by Prof. Ashutosh Dutta, and a research intern at the University of Maryland, College Park, working with Prof. Tianyi Zhou. My research interests center on efficient foundation models, with a specific focus on Mixture-of-Experts (MoE) and Test-Time Adaptation. My work aims to improve models’ generalization and efficiency. My current research focuses on LLM agents.

news

Aug 2026 🎓 Started my PhD journey at OSU NLP. Excited for this new chapter!
Jul 2026 🎉 Our paper “Routing Entropy: A Hidden Self-Verifier for Free in Mixture-of-Experts LLMs” has been accepted to COLM 2026! See you in San Francisco this October!
Jan 2026 🔥 Super excited to share that our paper “Routing Manifold Alignment Improves Generalization of MoE LLMs” has been accepted to ICLR 2026!
Aug 2025 🏆 Honored to receive the Travel Award from COLM 2025! I will also serve as a student volunteer at the conference in Montreal. See you there!
Jul 2025 ✈️ I will attend ICML 2025 in Vancouver to present our poster for R2-T2. Come say hi if you are around!
Jul 2025 🎉 Our paper C3PO (Critical-Layer, Core-Expert, Collaborative Pathway Optimization) has been accepted to COLM 2025!
Jun 2024 👨‍💻Started my research internship at the University of Maryland, College Park, advised by Prof. Tianyi Zhou. I will be working on efficient training and inference for MoE models.

selected publications

  1. routing-entropy.png
    Routing Entropy: A Hidden Self-Verifier for Free in Mixture-of-Experts LLMs
    Zhongyang Li, Ziyue Li, and Tianyi Zhou
    In Conference on Language Modeling (COLM), 2026
  2. quest.png
    QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks
    Jian Xie, Tianhe Lin, Zilu Wang, Yuting Ning, Yuekun Yao, Tianci Xue, Zhehao Zhang, Zhongyang Li, and 11 more authors
    In Advances in Neural Information Processing Systems (NeurIPS), 2026
  3. roma.png
    Routing Manifold Alignment Improves Generalization of Mixture-of-Experts LLMs
    Zhongyang Li, Ziyue Li, and Tianyi Zhou
    International Conference on Learning Representations (ICLR), 2026
  4. c3po.png
    C3PO: Critical-Layer, Core-Expert, Collaborative Pathway Optimization for Test-Time Expert Re-Mixing
    Zhongyang Li, Ziyue Li, and Tianyi Zhou
    In Conference on Language Modeling (COLM), 2025
  5. r2t2.png
    R2-T2: Re-Routing in Test-Time for Multimodal Mixture-of-Experts
    Zhongyang Li, Ziyue Li, and Tianyi Zhou
    In International Conference on Machine Learning (ICML), 2025