Stein Neural Sampler. - Tianyang Hu 001; Zixiang Chen; Hanxi Sun; Jincheng Bai; Mao Ye; Guang Cheng 003 (CoRR, 2018)

Optimal Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting. - Tianyang Hu 001; Zuofeng Shang; Guang Cheng 003 (CoRR, 2020)

Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network. - Tianyang Hu 001; Wenjia Wang; Cong Lin; Guang Cheng 003 (AISTATS, 2021)

ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. - Qishi Dong; Muhammad Awais; Fengwei Zhou; Chuanlong Xie; Tianyang Hu 001; Yongxin Yang; Sung-Ho Bae; Zhenguo Li (NeurIPS, 2022)

Understanding Square Loss in Training Overparametrized Neural Network Classifiers. - Tianyang Hu 001; Jun Wang 123; Wenjia Wang; Zhenguo Li (NeurIPS, 2022)

Inducing Neural Collapse in Deep Long-tailed Learning. - Xuantong Liu; Jianfeng Zhang; Tianyang Hu 001; He Cao; Yuan Yao 011; Lujia Pan (AISTATS, 2023)

ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning. - Hao Yang 044; Lanqing Hong; Aoxue Li; Tianyang Hu 001; Zhenguo Li; Gim Hee Lee; Liwei Wang 001 (CVPR, 2023)

Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. - Tianyang Hu 001; Zhili Liu; Fengwei Zhou; Wenjia Wang; Weiran Huang 001 (ICLR, 2023)

Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. - Yimeng Chen; Tianyang Hu 001; Fengwei Zhou; Zhenguo Li; Zhi-Ming Ma (ICML, 2023)

Complexity Matters: Rethinking the Latent Space for Generative Modeling. - Tianyang Hu 001; Fei Chen; Haonan Wang; Jiawei Li; Wenjia Wang; Jiacheng Sun; Zhenguo Li (NeurIPS, 2023)

Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models. - Weijian Luo; Tianyang Hu 001; Shifeng Zhang; Jiacheng Sun; Zhenguo Li; Zhihua Zhang (NeurIPS, 2023)

Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification. - Pawel Piwek; Adam Klukowski; Tianyang Hu 001 (UAI, 2023)

Boosting Visual-Language Models by Exploiting Hard Samples. - Haonan Wang; Minbin Huang; Runhui Huang; Lanqing Hong; Hang Xu 004; Tianyang Hu 001; Xiaodan Liang; Zhenguo Li (CoRR, 2023)

ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis. - Shoukang Hu; Kaichen Zhou; Kaiyu Li; Longhui Yu; Lanqing Hong; Tianyang Hu 001; Zhenguo Li; Gim Hee Lee; Ziwei Liu 002 (CoRR, 2023)

Training Energy-Based Models with Diffusion Contrastive Divergences. - Weijian Luo; Hao Jiang; Tianyang Hu 001; Jiacheng Sun; Zhenguo Li; Zhihua Zhang (CoRR, 2023)

Continual Learning by Modeling Intra-Class Variation. - Longhui Yu; Tianyang Hu 001; Lanqing Hong; Zhen Liu 019; Adrian Weller; Weiyang Liu (Trans. Mach. Learn. Res., 2023)

Accelerating Diffusion Sampling with Optimized Time Steps. - Shuchen Xue; Zhaoqiang Liu; Fei Chen; Shifeng Zhang; Tianyang Hu 001; Enze Xie; Zhenguo Li (CVPR, 2024)

JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation. - Chenhan Jiang; Yihan Zeng; Tianyang Hu 001; Songcun Xu; Wei Zhang 196; Hang Xu 004; Dit-Yan Yeung (ECCV (26), 2024)

Elucidating the design space of classifier-guided diffusion generation. - Jiajun Ma; Tianyang Hu 001; Wenjia Wang; Jiacheng Sun (ICLR, 2024)

Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. - Brian K. Chen; Tianyang Hu 001; Hui Jin; Hwee Kuan Lee; Kenji Kawaguchi (ICML, 2024)

Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. - Xuantong Liu; Tianyang Hu 001; Wenjia Wang; Kenji Kawaguchi; Yuan Yao 011 (ICML, 2024)

The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. - Jiajun Ma; Shuchen Xue; Tianyang Hu 001; Wenjia Wang; Zhaoqiang Liu; Zhenguo Li; Zhi-Ming Ma; Kenji Kawaguchi (ICML, 2024)

Deciphering the Projection Head: Representation Evaluation Self-supervised Learning. - Jiajun Ma; Tianyang Hu 001; Wenjia Wang (IJCAI, 2024)

On the Expressive Power of a Variant of the Looped Transformer. - Yihang Gao; Chuanyang Zheng; Enze Xie; Han Shi; Tianyang Hu 001; Yu Li 006; Michael K. Ng 001; Zhenguo Li; Zhaoqiang Liu (CoRR, 2024)

Random Smoothing Regularization in Kernel Gradient Descent Learning. - Liang Ding; Tianyang Hu 001; Jiahang Jiang; Donghao Li; Wenjia Wang; Yuan Yao 011 (J. Mach. Learn. Res., 2024)

Learning Few-Step Diffusion Models by Trajectory Distribution Matching. - Yihong Luo; Tianyang Hu 001; Jiacheng Sun; Yujun Cai; Jing Tang 004 (ICCV, 2025)

Adding Additional Control to One-Step Diffusion with Joint Distribution Matching. - Yihong Luo; Tianyang Hu 001; Yifan Song 006; Jiacheng Sun; Zhenguo Li; Jing Tang 004 (ICCV, 2025)

You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs. - Yihong Luo; Xiaolong Chen 003; Xinghua Qu; Tianyang Hu 001; Jing Tang 004 (ICLR, 2025)

Elucidating the design space of language models for image generation. - Xuantong Liu; Shaozhe Hao; Xianbiao Qi; Tianyang Hu 001; Jun Wang 123; Rong Xiao 003; Yuan Yao 011 (ICML, 2025)

Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data. - Haonan Wang; Minbin Huang; Runhui Huang; Lanqing Hong; Hang Xu 004; Tianyang Hu 001; Xiaodan Liang; Zhenguo Li; Hong Cheng 001; Kenji Kawaguchi (NAACL (Long Papers), 2025)

Reward-Instruct: A Reward-Centric Approach to Fast Photo-Realistic Image Generation. - Yihong Luo; Tianyang Hu 001; Weijian Luo; Kenji Kawaguchi; Jing Tang 004 (NeurIPS, 2025)

Noise Consistency Training: A Native Approach for One-step Generator in Learning Additional Controls. - Yihong Luo; Shuchen Xue; Tianyang Hu 001; Jing Tang 004 (NeurIPS, 2025)

Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary. - Tianyang Hu 001; Ruiqi Liu 003; Zuofeng Shang; Guang Cheng 003 (J. Mach. Learn. Res., 2025)

AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures. - Yihang Gao; Chuanyang Zheng; Enze Xie; Han Shi; Tianyang Hu 001; Yu Li 006; Michael Ng 001; Zhenguo Li; Zhaoqiang Liu (Trans. Mach. Learn. Res., 2025)

Rewards Are Enough for Fast Photo-Realistic Text-to-image Generation. - Yihong Luo; Tianyang Hu 001; Weijian Luo; Kenji Kawaguchi; Jing Tang 004 (CoRR, 2025)

Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling. - Tianyu Xie 001; Shuchen Xue; Zijin Feng; Tianyang Hu 001; Jiacheng Sun; Zhenguo Li; Cheng Zhang (CoRR, 2025)

Prefix-Tuning+: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention. - Haonan Wang; Brian K. Chen; Siquan Li; Xinhe Liang; Hwee Kuan Lee; Kenji Kawaguchi; Tianyang Hu 001 (CoRR, 2025)

Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture. - Shuchen Xue; Tianyu Xie 001; Tianyang Hu 001; Zijin Feng; Jiacheng Sun; Kenji Kawaguchi; Zhenguo Li; Zhi-Ming Ma (CoRR, 2025)

SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From. - Yao Tong; Haonan Wang; Siquan Li; Kenji Kawaguchi; Tianyang Hu 001 (CoRR, 2025)

Reinforcing Diffusion Models by Direct Group Preference Optimization. - Yihong Luo; Tianyang Hu 001; Jing Tang 004 (CoRR, 2025)

Transformers Are Born Biased: Structural Inductive Biases at Random Initialization and Their Practical Consequences. - Siquan Li; Yao Tong; Haonan Wang; Tianyang Hu 001 (CoRR, 2026)

TDM-R1: Reinforcing Few-Step Diffusion Models with Non-Differentiable Reward. - Yihong Luo; Tianyang Hu 001; Weijian Luo; Jing Tang 004 (CoRR, 2026)

Autoregressive Visual Generation Needs a Prologue. - Bowen Zheng; Weijian Luo; Guang Yang; Colin Zhang; Tianyang Hu 001 (CoRR, 2026)

Learning Discrete Autoregressive Priors with Wasserstein Gradient Flow. - Bowen Zheng; Yihong Luo; Tianyang Hu 001 (CoRR, 2026)

Taming the Entropy Cliff: Variable Codebook Size Quantization for Autoregressive Visual Generation. - Bowen Zheng; Weijian Luo; Guang Yang; Colin Zhang; Tianyang Hu 001 (CoRR, 2026)

The Structural Origin of Attention Sink: Variance Discrepancy, Super Neurons, and Dimension Disparity. - Siquan Li; Kaiqi Jiang; Jiacheng Sun; Tianyang Hu 001 (CoRR, 2026)