Chen-Hao Chao

Ph.D. in CS @ University of Toronto

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Hello, I'm a Computer Science Ph.D. student at the University of Toronto (UofT), advised by Prof. Rahul G. Krishnan. Prior to this, I completed my master's and bachelor's degrees in Computer Science at National Tsing Hua University (NTHU). I collaborated on research projects with Prof. Chun-Yi Lee, visited Prof. Zsolt Kira's lab at Georgia Tech, and interned at NVIDIA and MediaTek.

My current research explores efficient pre-training methods and scaling behavior of diffusion language models, developing approaches that improve training and sampling efficiency. More broadly, my work focuses on probabilistic modeling in generative AI, spanning both discrete and continuous generative methods (e.g., score-based and flow-based models) with applications to reinforcement learning, visual domain adaptation, and biological data visualization.

latest posts [full list]

selected publications [full list]

  1. Preprint
    MDM-Prime-v2: Binary Encoding and Index Shuffling Enable Compute-optimal Scaling of Diffusion Language Models
    Chen-Hao Chao, Wei-Fang Sun, Junwei Quan, and 2 more authors
    2026
  2. NeurIPS
    Beyond Masked and Unmasked: Discrete Diffusion Models via Partial Masking
    Chen-Hao Chao, Wei-Fang Sun, Hanwen Liang, and 2 more authors
    In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS) , 2025
  3. NeurIPS
    Maximum Entropy Reinforcement Learning via Energy-Based Normalizing Flow
    Chen-Hao Chao*, Chien Feng*, Wei-Fang Sun, and 3 more authors
    In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS) , 2024
  4. NeurIPS
    Training Energy-Based Normalizing Flow with Score-Matching Objectives
    Chen-Hao Chao, Wei-Fang Sun, Yen-Chang Hsu, and 2 more authors
    In Proceedings of the Conference on Neural Information Processing Systems (NeurIPS) , 2023
  5. ICML
    On Investigating the Conservative Property of Score-Based Generative Models
    Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, and 1 more author
    In Proceedings of the International Conference on Machine Learning (ICML) , 2023
  6. ICLR
    Denoising Likelihood Score Matching for Conditional Score-based Data Generation
    Chen-Hao Chao, Wei-Fang Sun, Bo-Wun Cheng, and 6 more authors
    In Proceedings of the International Conference on Learning Representations (ICLR) , 2022
  7. TPAMI
    Rainbow UDA: Combining Domain Adaptive Models for Semantic Segmentation Tasks
    Chen-Hao Chao, Bo-Wun Cheng, Tzu-Wen Wang*, and 2 more authors
    IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2023