Zanlin Ni

prof_pic.jpg

Tsinghua University

Beijing, China

nzl22@mails.tsinghua.edu.cn

I am a Ph.D. student in Pattern Recognition and Machine Learning at LeapLab, Tsinghua University, advised by Prof. Gao Huang. I received my B.Eng. in Automation from Tsinghua University in 2022.

My research focuses on efficient generative models, with a particular emphasis on discrete generative models and diffusion language models.

My work has appeared in top-tier venues including CVPR, ICCV, NeurIPS, ECCV, ICLR, TPAMI, IJCV, and Nature Machine Intelligence.

Previously, I was a research intern at BAAI (Oct. 2022 - May. 2023). During this time, I led the implementation of MUSE-Pytorch, an open-source reproduction of Google’s Muse. This codebase has served as a reference for subsequent projects such as 1d-tokenizer and StyleDrop-Pytorch.

news

Jan 13, 2026 🎉 New preprint The Flexibility Trap is out! Check out our project page.
Oct 27, 2025 🎉 Our paper AdaGen (TPAMI 2025) is accepted!
Oct 14, 2025 🎉 Received the National Scholarship from Tsinghua University in 2025!

selected publications

  1. Preprint
    FlexibilityTrap.png
    The Flexibility Trap: Rethinking the Value of Arbitrary Order in Diffusion Language Models
    Zanlin Ni, Shenzhi Wang, Yang Yue, and 8 more authors
    2026
    PDF Code Model Website
  2. TPAMI
    AdaGen.png
    AdaGen: Learning Adaptive Policy for Image Synthesis
    Zanlin Ni*, Yulin Wang, Yeguo Hua, and 5 more authors
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025
  3. ICCV
    CODA.png
    CODA: Repurposing Continuous VAEs for Discrete Tokenization
    Zeyu Liu*, Zanlin Ni*, Yeguo Hua, and 4 more authors
    In IEEE/CVF International Conference on Computer Vision (ICCV), 2025
    arXiv Code
  4. NeurIPS
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    ENAT: Rethinking Spatial-Temporal Interactions in Token-Based Image Synthesis
    Zanlin Ni*, Yulin Wang, Renping Zhou, and 5 more authors
    In Advances in Neural Information Processing Systems (NeurIPS), 2024
    arXiv Code
  5. ECCV
    AdaNAT.png
    AdaNAT: Exploring Adaptive Policy for Token-Based Image Generation
    Zanlin Ni*, Yulin Wang, Renping Zhou, and 6 more authors
    In European Conference on Computer Vision (ECCV), 2024
    arXiv Code
  6. CVPR
    AutoNAT.png
    Revisiting Non-Autoregressive Transformers for Efficient Image Synthesis
    Zanlin Ni*, Yulin Wang, Renping Zhou, and 6 more authors
    In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2024
    arXiv Code
  7. NMI
    AdaptiveNN.png
    Emulating Human-like Adaptive Vision for Efficient and Flexible Machine Visual Perception
    Yulin Wang, Yang Yue, Huanqian Wang, and 10 more authors
    Nature Machine Intelligence (NMI), 2025
    arXiv Code
  8. IJCV
    InfoPro_IJCV.png
    InfoPro: Locally Supervised Deep Learning by Maximizing Information Propagation
    Yulin Wang*, Zanlin Ni*, Yifan Pu, and 4 more authors
    International Journal of Computer Vision (IJCV), 2025
    arXiv Code
  9. ECCV
    LLaVA-UHD: An LMM Perceiving Any Aspect Ratio and High-Resolution Images
    Ruyi Xu, Yuan Yao, Zonghao Guo, and 7 more authors
    In European Conference on Computer Vision (ECCV), 2024
    arXiv Code
  10. ICCV
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    Deep Incubation: Training Large Models by Divide-and-Conquering
    Zanlin Ni*, Yulin Wang, Jiangwei Yu, and 3 more authors
    In IEEE/CVF International Conference on Computer Vision (ICCV), 2023
    arXiv Code
  11. ICLR
    InfoPro_ICLR.png
    Revisiting Locally Supervised Learning: An Alternative to End-to-End Training
    Yulin Wang, Zanlin Ni, Shiji Song, and 2 more authors
    In International Conference on Learning Representations (ICLR), 2021
    arXiv Code
  12. CVPR
    USDL.png
    Uncertainty-Aware Score Distribution Learning for Action Quality Assessment
    Yansong Tang*, Zanlin Ni*, Jiangbo Zhou, and 4 more authors
    In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2020
    arXiv Code