publications

* denotes equal contribution.

2026

  1. ICML 2026
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    In-Context Universal Approximation, Compositional Generalization, and Algorithm Emulation
    Jerry Yao-Chieh Hu*, Hong-Yu Chen*, Po-Chiao Lin*, Maojiang Su, and Han Liu
    In International Conference on Machine Learning, 2026
  2. ICML 2026
    Universal Approximation with Softmax Attention
    Jerry Yao-Chieh Hu*, Hude Liu*, Hong-Yu Chen*, Weimin Wu, and Han Liu
    In International Conference on Machine Learning, 2026
    arXiv
  3. ICML 2026
    Chain-of-Thought Gradient Descent
    Hong-Yu Chen*, Venkat Sripad Ganti*, Jerry Yao-Chieh Hu, Hude Liu, and Han Liu
    In International Conference on Machine Learning, 2026
  4. ICML 2026
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    StarEmbed: Benchmarking Time Series Foundation Models on Astronomical Observations of Variable Stars
    Weijian Li*, Hong-Yu Chen*, Nabeel Rehemtulla*, Ved G. Shah, Dennis Wu, Dongho Kim, Qinjie Lin, Adam A. Miller, and Han Liu
    In International Conference on Machine Learning, 2026
    AI4Physics Workshop Outstanding Paper arXiv Code Website

2025

  1. arXiv
    Transformers versus the EM Algorithm in Multi-class Clustering
    Yihan He, Hong-Yu Chen, Yuan Cao, Jianqing Fan, and Han Liu
    arXiv preprint arXiv:2502.06007, 2025
    arXiv
  2. arXiv
    Learning spectral methods by transformers
    Yihan He, Yuan Cao, Hong-Yu Chen, Dennis Wu, Jianqing Fan, and Han Liu
    arXiv preprint arXiv:2501.01312, 2025
    arXiv
  3. arXiv
    Transformers Simulate MLE for Sequence Generation in Bayesian Networks
    Yuan Cao, Yihan He, Dennis Wu, Hong-Yu Chen, Jianqing Fan, and Han Liu
    arXiv preprint arXiv:2501.02547, 2025
    arXiv

2024

  1. ICML 2024
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    Outlier-Efficient Hopfield Layers for Large Transformer-Based Models
    Jerry Yao-Chieh Hu, Pei-Hsuan Chang, Haozheng Luo, Hong-Yu Chen, Weijian Li, Wei-Po Wang, and Han Liu
    In International Conference on Machine Learning, 2024
    arXiv PDF Code Poster Slides