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ORCIDTianyang Hu 0001
Person information
- affiliation: Chinese University of Hong Kong - Shenzhen (CUHK-SZ), School of Data Science, Shenzhen, China
- affiliation (former): National University of Singapore, Singapore
- affiliation (former, PhD): Purdue University, West Lafayette, IN, USA
Other persons with the same name
- Tianyang Hu — disambiguation page
- Tianyang Hu 0002 — University of Texas at Arlington, TX, USA
- Tianyang Hu 0003
![[0009-0006-8814-2215]](https://dblp.org/img/orcid-mark.12x12.png "0009-0006-8814-2215")
— Beihang University, SNARS Laboratory, Beijing, China
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2020 – today
- 2025
[j2]Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael Ng, Zhenguo Li, Zhaoqiang Liu:
AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures. Trans. Mach. Learn. Res. 2025 (2025)- [c20]Yihong Luo, Xiaolong Chen, Xinghua Qu, Tianyang Hu, Jing Tang:
You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs. ICLR 2025 - [c19]Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu, Jun Wang, Rong Xiao, Yuan Yao:
Elucidating the design space of language models for image generation. ICML 2025 - [c18]Haonan Wang, Minbin Huang, Runhui Huang, Lanqing Hong, Hang Xu, Tianyang Hu, Xiaodan Liang, Zhenguo Li, Hong Cheng, Kenji Kawaguchi:
Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data. NAACL (Long Papers) 2025: 7854-7873 - [i35]Yihong Luo, Tianyang Hu, Yifan Song, Jiacheng Sun, Zhenguo Li, Jing Tang:
Adding Additional Control to One-Step Diffusion with Joint Distribution Matching. CoRR abs/2503.06652 (2025) - [i34]Yihong Luo, Tianyang Hu, Jiacheng Sun, Yujun Cai, Jing Tang:
Learning Few-Step Diffusion Models by Trajectory Distribution Matching. CoRR abs/2503.06674 (2025) - [i33]Yihong Luo, Tianyang Hu, Weijian Luo, Kenji Kawaguchi, Jing Tang:
Rewards Are Enough for Fast Photo-Realistic Text-to-image Generation. CoRR abs/2503.13070 (2025) - [i32]Tianyu Xie, Shuchen Xue, Zijin Feng, Tianyang Hu, Jiacheng Sun, Zhenguo Li, Cheng Zhang:
Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling. CoRR abs/2505.17384 (2025) - [i31]Haonan Wang, Brian K. Chen, Siquan Li, Xinhe Liang, Hwee Kuan Lee, Kenji Kawaguchi, Tianyang Hu:
Prefix-Tuning+: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention. CoRR abs/2506.13674 (2025) - [i30]Yihong Luo, Shuchen Xue, Tianyang Hu, Jing Tang:
Noise Consistency Training: A Native Approach for One-Step Generator in Learning Additional Controls. CoRR abs/2506.19741 (2025) - [i29]Shuchen Xue, Tianyu Xie, Tianyang Hu, Zijin Feng, Jiacheng Sun, Kenji Kawaguchi, Zhenguo Li, Zhi-Ming Ma:
Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture. CoRR abs/2506.19935 (2025) - [i28]Yao Tong, Haonan Wang, Siquan Li, Kenji Kawaguchi, Tianyang Hu:
SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From. CoRR abs/2509.26404 (2025) - [i27]Yihong Luo, Tianyang Hu, Jing Tang:
Reinforcing Diffusion Models by Direct Group Preference Optimization. CoRR abs/2510.08425 (2025) - 2024
- [c17]Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li:
Accelerating Diffusion Sampling with Optimized Time Steps. CVPR 2024: 8292-8301 - [c16]Chenhan Jiang, Yihan Zeng, Tianyang Hu, Songcun Xu, Wei Zhang, Hang Xu, Dit-Yan Yeung:
JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation. ECCV (26) 2024: 439-456 - [c15]Jiajun Ma, Tianyang Hu, Wenjia Wang, Jiacheng Sun:
Elucidating the design space of classifier-guided diffusion generation. ICLR 2024 - [c14]Brian K. Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi:
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. ICML 2024: 6833-6846 - [c13]Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao:
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. ICML 2024: 31165-31185 - [c12]Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi:
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. ICML 2024: 34053-34074 - [c11]Jiajun Ma, Tianyang Hu, Wenjia Wang:
Deciphering the Projection Head: Representation Evaluation Self-supervised Learning. IJCAI 2024: 4724-4732 - [i26]Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael K. Ng, Zhenguo Li, Zhaoqiang Liu:
On the Expressive Power of a Variant of the Looped Transformer. CoRR abs/2402.13572 (2024) - [i25]Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi:
The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. CoRR abs/2402.15170 (2024) - [i24]Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao:
Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. CoRR abs/2402.16305 (2024) - [i23]Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li:
Accelerating Diffusion Sampling with Optimized Time Steps. CoRR abs/2402.17376 (2024) - [i22]Brian K. Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi:
Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. CoRR abs/2406.02847 (2024) - [i21]Chenhan Jiang, Yihan Zeng, Tianyang Hu, Songcun Xu, Wei Zhang, Hang Xu, Dit-Yan Yeung:
JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation. CoRR abs/2407.12291 (2024) - [i20]Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu, Jun Wang, Rong Xiao, Yuan Yao:
Elucidating the design space of language models for image generation. CoRR abs/2410.16257 (2024) - 2023
- [j1]Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu:
Continual Learning by Modeling Intra-Class Variation. Trans. Mach. Learn. Res. 2023 (2023) - [c10]Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Yuan Yao, Lujia Pan:
Inducing Neural Collapse in Deep Long-tailed Learning. AISTATS 2023: 11534-11544 - [c9]Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, Liwei Wang:
ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning. CVPR 2023: 16508-16517 - [c8]Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang:
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. ICLR 2023 - [c7]Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhi-Ming Ma:
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. ICML 2023: 4623-4640 - [c6]Tianyang Hu, Fei Chen, Haonan Wang, Jiawei Li, Wenjia Wang, Jiacheng Sun, Zhenguo Li:
Complexity Matters: Rethinking the Latent Space for Generative Modeling. NeurIPS 2023 - [c5]Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhihua Zhang:
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models. NeurIPS 2023 - [c4]Pawel Piwek, Adam Klukowski, Tianyang Hu:
Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification. UAI 2023: 1673-1683 - [i19]Jiajun Ma, Tianyang Hu, Wenjia Wang:
Deciphering the Projection Head: Representation Evaluation Self-supervised Learning. CoRR abs/2301.12189 (2023) - [i18]Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Lujia Pan, Yuan Yao:
Inducing Neural Collapse in Deep Long-tailed Learning. CoRR abs/2302.12453 (2023) - [i17]Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, Liwei Wang:
ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning. CoRR abs/2303.11052 (2023) - [i16]Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan Yao:
Random Smoothing Regularization in Kernel Gradient Descent Learning. CoRR abs/2305.03531 (2023) - [i15]Haonan Wang, Minbin Huang, Runhui Huang, Lanqing Hong, Hang Xu, Tianyang Hu, Xiaodan Liang, Zhenguo Li:
Boosting Visual-Language Models by Exploiting Hard Samples. CoRR abs/2305.05208 (2023) - [i14]Shoukang Hu, Kaichen Zhou, Kaiyu Li, Longhui Yu, Lanqing Hong, Tianyang Hu, Zhenguo Li, Gim Hee Lee, Ziwei Liu:
ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis. CoRR abs/2305.11031 (2023) - [i13]Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhihua Zhang:
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models. CoRR abs/2305.18455 (2023) - [i12]Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhiming Ma:
Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. CoRR abs/2306.02595 (2023) - [i11]Pawel Piwek, Adam Klukowski, Tianyang Hu:
Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification. CoRR abs/2306.08805 (2023) - [i10]Weijian Luo, Hao Jiang, Tianyang Hu, Jiacheng Sun, Zhenguo Li, Zhihua Zhang:
Training Energy-Based Models with Diffusion Contrastive Divergences. CoRR abs/2307.01668 (2023) - [i9]Tianyang Hu, Fei Chen, Haonan Wang, Jiawei Li, Wenjia Wang, Jiacheng Sun, Zhenguo Li:
Complexity Matters: Rethinking the Latent Space for Generative Modeling. CoRR abs/2307.08283 (2023) - [i8]Jiajun Ma, Tianyang Hu, Wenjia Wang, Jiacheng Sun:
Elucidating The Design Space of Classifier-Guided Diffusion Generation. CoRR abs/2310.11311 (2023) - 2022
- [c3]Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li:
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. NeurIPS 2022 - [c2]Tianyang Hu, Jun Wang, Wenjia Wang, Zhenguo Li:
Understanding Square Loss in Training Overparametrized Neural Network Classifiers. NeurIPS 2022 - [i7]Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang:
Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. CoRR abs/2205.14814 (2022) - [i6]Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu:
Continual Learning by Modeling Intra-Class Variation. CoRR abs/2210.05398 (2022) - [i5]Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li:
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. CoRR abs/2210.09236 (2022) - 2021
- [c1]Tianyang Hu, Wenjia Wang, Cong Lin, Guang Cheng:
Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network. AISTATS 2021: 829-837 - [i4]Tianyang Hu, Jun Wang, Wenjia Wang, Zhenguo Li:
Understanding Square Loss in Training Overparametrized Neural Network Classifiers. CoRR abs/2112.03657 (2021) - 2020
- [i3]Tianyang Hu, Zuofeng Shang, Guang Cheng:
Optimal Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting. CoRR abs/2001.06892 (2020) - [i2]Wenjia Wang, Tianyang Hu, Cong Lin, Guang Cheng:
Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network. CoRR abs/2007.02486 (2020)
2010 – 2019
- 2018
- [i1]Tianyang Hu, Zixiang Chen, Hanxi Sun, Jincheng Bai, Mao Ye, Guang Cheng:
Stein Neural Sampler. CoRR abs/1810.03545 (2018)
Coauthor Index
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