Tianyang Hu - RankMe

61 papers A* 15A 3Journal 41Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	TDM-R1: Reinforcing Few-Step Diffusion Models with Non-Differentiable Reward. CoRR Yihong Luo, Tianyang Hu, Weijian Luo, Jing Tang
2026	J	`jnl`	Transformers Are Born Biased: Structural Inductive Biases at Random Initialization and Their Practical Consequences. CoRR Siquan Li, Yao Tong, Haonan Wang, Tianyang Hu
2025	J	`jnl`	Adding Additional Control to One-Step Diffusion with Joint Distribution Matching. CoRR Yihong Luo, Tianyang Hu, Yifan Song, Jiacheng Sun, Zhenguo Li, Jing Tang
2025	J	`jnl`	AlgoFormer: An Efficient Transformer Framework with Algorithmic Structures. Trans. Mach. Learn. Res. Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael Ng, Zhenguo Li, Zhaoqiang Liu
2025	J	`jnl`	Any-Order GPT as Masked Diffusion Model: Decoupling Formulation and Architecture. CoRR Shuchen Xue, Tianyu Xie, Tianyang Hu, Zijin Feng, Jiacheng Sun, Kenji Kawaguchi, Zhenguo Li, Zhi-Ming Ma
2025	A*	`conf`	Elucidating the design space of language models for image generation. ICML Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu, Jun Wang, Rong Xiao, Yuan Yao
2025	—	`conf`	Getting More Juice Out of Your Data: Hard Pair Refinement Enhances Visual-Language Models Without Extra Data. NAACL (Long Papers) Haonan Wang, Minbin Huang, Runhui Huang, Lanqing Hong, Hang Xu, Tianyang Hu, Xiaodan Liang, Zhenguo Li, Hong Cheng, Kenji Kawaguchi
2025	J	`jnl`	Learning Few-Step Diffusion Models by Trajectory Distribution Matching. CoRR Yihong Luo, Tianyang Hu, Jiacheng Sun, Yujun Cai, Jing Tang
2025	J	`jnl`	Minimax Optimal Deep Neural Network Classifiers Under Smooth Decision Boundary. J. Mach. Learn. Res. Tianyang Hu, Ruiqi Liu, Zuofeng Shang, Guang Cheng
2025	J	`jnl`	Noise Consistency Training: A Native Approach for One-Step Generator in Learning Additional Controls. CoRR Yihong Luo, Shuchen Xue, Tianyang Hu, Jing Tang
2025	J	`jnl`	Prefix-Tuning+: Modernizing Prefix-Tuning by Decoupling the Prefix from Attention. CoRR Haonan Wang, Brian K. Chen, Siquan Li, Xinhe Liang, Hwee Kuan Lee, Kenji Kawaguchi, Tianyang Hu
2025	J	`jnl`	Reinforcing Diffusion Models by Direct Group Preference Optimization. CoRR Yihong Luo, Tianyang Hu, Jing Tang
2025	J	`jnl`	Rewards Are Enough for Fast Photo-Realistic Text-to-image Generation. CoRR Yihong Luo, Tianyang Hu, Weijian Luo, Kenji Kawaguchi, Jing Tang
2025	J	`jnl`	SeedPrints: Fingerprints Can Even Tell Which Seed Your Large Language Model Was Trained From. CoRR Yao Tong, Haonan Wang, Siquan Li, Kenji Kawaguchi, Tianyang Hu
2025	J	`jnl`	Variational Autoencoding Discrete Diffusion with Enhanced Dimensional Correlations Modeling. CoRR Tianyu Xie, Shuchen Xue, Zijin Feng, Tianyang Hu, Jiacheng Sun, Zhenguo Li, Cheng Zhang
2025	A*	`conf`	You Only Sample Once: Taming One-Step Text-to-Image Synthesis by Self-Cooperative Diffusion GANs. ICLR Yihong Luo, Xiaolong Chen, Xinghua Qu, Tianyang Hu, Jing Tang
2024	A*	`conf`	Accelerating Diffusion Sampling with Optimized Time Steps. CVPR Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li
2024	J	`jnl`	Accelerating Diffusion Sampling with Optimized Time Steps. CoRR Shuchen Xue, Zhaoqiang Liu, Fei Chen, Shifeng Zhang, Tianyang Hu, Enze Xie, Zhenguo Li
2024	A*	`conf`	Deciphering the Projection Head: Representation Evaluation Self-supervised Learning. IJCAI Jiajun Ma, Tianyang Hu, Wenjia Wang
2024	A*	`conf`	Elucidating the design space of classifier-guided diffusion generation. ICLR Jiajun Ma, Tianyang Hu, Wenjia Wang, Jiacheng Sun
2024	J	`jnl`	Elucidating the design space of language models for image generation. CoRR Xuantong Liu, Shaozhe Hao, Xianbiao Qi, Tianyang Hu, Jun Wang, Rong Xiao, Yuan Yao
2024	A*	`conf`	Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. ICML Brian K. Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi
2024	J	`jnl`	Exact Conversion of In-Context Learning to Model Weights in Linearized-Attention Transformers. CoRR Brian K. Chen, Tianyang Hu, Hui Jin, Hwee Kuan Lee, Kenji Kawaguchi
2024	—	`conf`	JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation. ECCV (26) Chenhan Jiang, Yihan Zeng, Tianyang Hu, Songcun Xu, Wei Zhang, Hang Xu, Dit-Yan Yeung
2024	J	`jnl`	JointDreamer: Ensuring Geometry Consistency and Text Congruence in Text-to-3D Generation via Joint Score Distillation. CoRR Chenhan Jiang, Yihan Zeng, Tianyang Hu, Songcun Xu, Wei Zhang, Hang Xu, Dit-Yan Yeung
2024	J	`jnl`	On the Expressive Power of a Variant of the Looped Transformer. CoRR Yihang Gao, Chuanyang Zheng, Enze Xie, Han Shi, Tianyang Hu, Yu Li, Michael K. Ng, Zhenguo Li, Zhaoqiang Liu
2024	J	`jnl`	Random Smoothing Regularization in Kernel Gradient Descent Learning. J. Mach. Learn. Res. Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan Yao
2024	A*	`conf`	Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. ICML Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao
2024	J	`jnl`	Referee Can Play: An Alternative Approach to Conditional Generation via Model Inversion. CoRR Xuantong Liu, Tianyang Hu, Wenjia Wang, Kenji Kawaguchi, Yuan Yao
2024	A*	`conf`	The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. ICML Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi
2024	J	`jnl`	The Surprising Effectiveness of Skip-Tuning in Diffusion Sampling. CoRR Jiajun Ma, Shuchen Xue, Tianyang Hu, Wenjia Wang, Zhaoqiang Liu, Zhenguo Li, Zhi-Ming Ma, Kenji Kawaguchi
2023	J	`jnl`	Boosting Visual-Language Models by Exploiting Hard Samples. CoRR Haonan Wang, Minbin Huang, Runhui Huang, Lanqing Hong, Hang Xu, Tianyang Hu, Xiaodan Liang, Zhenguo Li
2023	A*	`conf`	Complexity Matters: Rethinking the Latent Space for Generative Modeling. NeurIPS Tianyang Hu, Fei Chen, Haonan Wang, Jiawei Li, Wenjia Wang, Jiacheng Sun, Zhenguo Li
2023	J	`jnl`	Complexity Matters: Rethinking the Latent Space for Generative Modeling. CoRR Tianyang Hu, Fei Chen, Haonan Wang, Jiawei Li, Wenjia Wang, Jiacheng Sun, Zhenguo Li
2023	J	`jnl`	ConsistentNeRF: Enhancing Neural Radiance Fields with 3D Consistency for Sparse View Synthesis. CoRR Shoukang Hu, Kaichen Zhou, Kaiyu Li, Longhui Yu, Lanqing Hong, Tianyang Hu, Zhenguo Li, Gim Hee Lee, Ziwei Liu
2023	J	`jnl`	Continual Learning by Modeling Intra-Class Variation. Trans. Mach. Learn. Res. Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu
2023	A*	`conf`	ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning. CVPR Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, Liwei Wang
2023	J	`jnl`	ContraNeRF: Generalizable Neural Radiance Fields for Synthetic-to-real Novel View Synthesis via Contrastive Learning. CoRR Hao Yang, Lanqing Hong, Aoxue Li, Tianyang Hu, Zhenguo Li, Gim Hee Lee, Liwei Wang
2023	J	`jnl`	Deciphering the Projection Head: Representation Evaluation Self-supervised Learning. CoRR Jiajun Ma, Tianyang Hu, Wenjia Wang
2023	A*	`conf`	Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models. NeurIPS Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhihua Zhang
2023	J	`jnl`	Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models. CoRR Weijian Luo, Tianyang Hu, Shifeng Zhang, Jiacheng Sun, Zhenguo Li, Zhihua Zhang
2023	J	`jnl`	Elucidating The Design Space of Classifier-Guided Diffusion Generation. CoRR Jiajun Ma, Tianyang Hu, Wenjia Wang, Jiacheng Sun
2023	A	`conf`	Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification. UAI Pawel Piwek, Adam Klukowski, Tianyang Hu
2023	J	`jnl`	Exact Count of Boundary Pieces of ReLU Classifiers: Towards the Proper Complexity Measure for Classification. CoRR Pawel Piwek, Adam Klukowski, Tianyang Hu
2023	A*	`conf`	Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. ICML Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhi-Ming Ma
2023	J	`jnl`	Explore and Exploit the Diverse Knowledge in Model Zoo for Domain Generalization. CoRR Yimeng Chen, Tianyang Hu, Fengwei Zhou, Zhenguo Li, Zhiming Ma
2023	A	`conf`	Inducing Neural Collapse in Deep Long-tailed Learning. AISTATS Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Yuan Yao, Lujia Pan
2023	J	`jnl`	Inducing Neural Collapse in Deep Long-tailed Learning. CoRR Xuantong Liu, Jianfeng Zhang, Tianyang Hu, He Cao, Lujia Pan, Yuan Yao
2023	J	`jnl`	Random Smoothing Regularization in Kernel Gradient Descent Learning. CoRR Liang Ding, Tianyang Hu, Jiahang Jiang, Donghao Li, Wenjia Wang, Yuan Yao
2023	J	`jnl`	Training Energy-Based Models with Diffusion Contrastive Divergences. CoRR Weijian Luo, Hao Jiang, Tianyang Hu, Jiacheng Sun, Zhenguo Li, Zhihua Zhang
2023	A*	`conf`	Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. ICLR Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang
2022	J	`jnl`	Continual Learning by Modeling Intra-Class Variation. CoRR Longhui Yu, Tianyang Hu, Lanqing Hong, Zhen Liu, Adrian Weller, Weiyang Liu
2022	A*	`conf`	Understanding Square Loss in Training Overparametrized Neural Network Classifiers. NeurIPS Tianyang Hu, Jun Wang, Wenjia Wang, Zhenguo Li
2022	J	`jnl`	Your Contrastive Learning Is Secretly Doing Stochastic Neighbor Embedding. CoRR Tianyang Hu, Zhili Liu, Fengwei Zhou, Wenjia Wang, Weiran Huang
2022	A*	`conf`	ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. NeurIPS Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li
2022	J	`jnl`	ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization. CoRR Qishi Dong, Muhammad Awais, Fengwei Zhou, Chuanlong Xie, Tianyang Hu, Yongxin Yang, Sung-Ho Bae, Zhenguo Li
2021	A	`conf`	Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network. AISTATS Tianyang Hu, Wenjia Wang, Cong Lin, Guang Cheng
2021	J	`jnl`	Understanding Square Loss in Training Overparametrized Neural Network Classifiers. CoRR Tianyang Hu, Jun Wang, Wenjia Wang, Zhenguo Li
2020	J	`jnl`	Optimal Rate of Convergence for Deep Neural Network Classifiers under the Teacher-Student Setting. CoRR Tianyang Hu, Zuofeng Shang, Guang Cheng
2020	J	`jnl`	Regularization Matters: A Nonparametric Perspective on Overparametrized Neural Network. CoRR Wenjia Wang, Tianyang Hu, Cong Lin, Guang Cheng
2018	J	`jnl`	Stein Neural Sampler. CoRR Tianyang Hu, Zixiang Chen, Hanxi Sun, Jincheng Bai, Mao Ye, Guang Cheng