Chongxuan Li - RankMe

162 papers A* 50Misc 1Journal 100Unranked 11

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Causal Forcing: Autoregressive Diffusion Distillation Done Right for High-Quality Real-Time Interactive Video Generation. CoRR Hongzhou Zhu, Min Zhao, Guande He, Hang Su, Chongxuan Li, Jun Zhu
2026	J	`jnl`	DLLM-Searcher: Adapting Diffusion Large Language Model for Search Agents. CoRR Jiahao Zhao, Shaoxuan Xu, Zhongxiang Sun, Fengqi Zhu, Jingyang Ou, Yuling Shi, Chongxuan Li, Xiao Zhang, Jun Xu
2026	J	`jnl`	LLaDA-o: An Effective and Length-Adaptive Omni Diffusion Model. CoRR Zebin You, Xiaolu Zhang, Jun Zhou, Chongxuan Li, Ji-Rong Wen
2026	J	`jnl`	Optimization and Generation in Aerodynamics Inverse Design. CoRR Huaguan Chen, Ning Lin, Luxi Chen, Rui Zhang, Wenbing Huang, Chongxuan Li, Hao Sun
2026	J	`jnl`	Spectral Condition for μP under Width-Depth Scaling. CoRR Chenyu Zheng, Rongzhen Wang, Xinyu Zhang, Chongxuan Li
2025	J	`jnl`	A Survey on Latent Reasoning. CoRR Ruijie Zhu, Tianhao Peng, Tianhao Cheng, Xingwei Qu, Jinfa Huang, Dawei Zhu, Hao Wang, Kaiwen Xue, Xuanliang Zhang, Yong Shan, Tianle Cai, Taylor Kergan, Assel Kembay, Andrew Smith, Chenghua Lin, Binh Nguyen, Yuqi Pan, Yuhong Chou, Zefan Cai, Zhenhe Wu, Yongchi Zhao, Tianyu Liu, Jian Yang, Wangchunshu Zhou, Chujie Zheng, Chongxuan Li, Yuyin Zhou, Zhoujun Li, Zhaoxiang Zhang, Jiaheng Liu, Ge Zhang, Wenhao Huang, Jason Eshraghian
2025	A*	`conf`	A Theory for Conditional Generative Modeling on Multiple Data Sources. ICML Rongzhen Wang, Yan Zhang, Chenyu Zheng, Chongxuan Li, Guoqiang Wu
2025	J	`jnl`	A Theory for Conditional Generative Modeling on Multiple Data Sources. CoRR Rongzhen Wang, Yan Zhang, Chenyu Zheng, Chongxuan Li, Guoqiang Wu
2025	A*	`conf`	Animate and Sound an Image. CVPR Xihua Wang, Ruihua Song, Chongxuan Li, Xin Cheng, Boyuan Li, Yihan Wu, Yuyue Wang, Hongteng Xu, Yunfeng Wang
2025	A*	`conf`	Are Images Indistinguishable to Humans Also Indistinguishable to Classifiers? CVPR Zebin You, Xinyu Zhang, Hanzhong Guo, Jingdong Wang, Chongxuan Li
2025	—	`conf`	Concat-ID: Towards Universal Identity-Preserving Video Synthesis. ICCVW Yong Zhong, Zhuoyi Yang, Jiayan Teng, Xiaotao Gu, Chongxuan Li
2025	J	`jnl`	Concat-ID: Towards Universal Identity-Preserving Video Synthesis. CoRR Yong Zhong, Zhuoyi Yang, Jiayan Teng, Xiaotao Gu, Chongxuan Li
2025	J	`jnl`	ControlVideo: conditional control for one-shot text-driven video editing and beyond. Sci. China Inf. Sci. Min Zhao, Rongzhen Wang, Fan Bao, Chongxuan Li, Jun Zhu
2025	J	`jnl`	DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models. Mach. Intell. Res. Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
2025	A*	`conf`	Effective and Efficient Masked Image Generation Models. ICML Zebin You, Jingyang Ou, Xiaolu Zhang, Jun Hu, Jun Zhou, Chongxuan Li
2025	J	`jnl`	Effective and Efficient Masked Image Generation Models. CoRR Zebin You, Jingyang Ou, Xiaolu Zhang, Jun Hu, Jun Zhou, Chongxuan Li
2025	J	`jnl`	FlexWorld: Progressively Expanding 3D Scenes for Flexiable-View Synthesis. CoRR Luxi Chen, Zihan Zhou, Min Zhao, Yikai Wang, Ge Zhang, Wenhao Huang, Hao Sun, Ji-Rong Wen, Chongxuan Li
2025	A*	`conf`	Improving Long-Text Alignment for Text-to-Image Diffusion Models. ICLR Luping Liu, Chao Du, Tianyu Pang, Zehan Wang, Chongxuan Li, Dong Xu
2025	J	`jnl`	LLaDA 1.5: Variance-Reduced Preference Optimization for Large Language Diffusion Models. CoRR Fengqi Zhu, Rongzhen Wang, Shen Nie, Xiaolu Zhang, Chunwei Wu, Jun Hu, Jun Zhou, Jianfei Chen, Yankai Lin, Ji-Rong Wen, Chongxuan Li
2025	J	`jnl`	LLaDA-MoE: A Sparse MoE Diffusion Language Model. CoRR Fengqi Zhu, Zebin You, Yipeng Xing, Zenan Huang, Lin Liu, Yihong Zhuang, Guoshan Lu, Kangyu Wang, Xudong Wang, Lanning Wei, Hongrui Guo, Jiaqi Hu, Wentao Ye, Tieyuan Chen, Chenchen Li, Chengfu Tang, Haibo Feng, Jun Hu, Jun Zhou, Xiaolu Zhang, Zhenzhong Lan, Junbo Zhao, Da Zheng, Chongxuan Li, Jianguo Li, Ji-Rong Wen
2025	J	`jnl`	LLaDA-Rec: Discrete Diffusion for Parallel Semantic ID Generation in Generative Recommendation. CoRR Teng Shi, Chenglei Shen, Weijie Yu, Shen Nie, Chongxuan Li, Xiao Zhang, Ming He, Yan Han, Jun Xu
2025	J	`jnl`	LLaDA-V: Large Language Diffusion Models with Visual Instruction Tuning. CoRR Zebin You, Shen Nie, Xiaolu Zhang, Jun Hu, Jun Zhou, Zhiwu Lu, Ji-Rong Wen, Chongxuan Li
2025	J	`jnl`	LLaDA2.0: Scaling Up Diffusion Language Models to 100B. CoRR Tiwei Bie, Maosong Cao, Kun Chen, Lun Du, Mingliang Gong, Zhuochen Gong, Yanmei Gu, Jiaqi Hu, Zenan Huang, Zhenzhong Lan, Chengxi Li, Chongxuan Li, Jianguo Li, Zehuan Li, Huabin Liu, Lin Liu, Guoshan Lu, Xiaocheng Lu, Yuxin Ma, Jianfeng Tan, Lanning Wei, Ji-Rong Wen, Yipeng Xing, Xiaolu Zhang, Junbo Zhao, Da Zheng, Jun Zhou, Junlin Zhou, Zhanchao Zhou, Liwang Zhu, Yihong Zhuang
2025	J	`jnl`	Large Language Diffusion Models. CoRR Shen Nie, Fengqi Zhu, Zebin You, Xiaolu Zhang, Jingyang Ou, Jun Hu, Jun Zhou, Yankai Lin, Ji-Rong Wen, Chongxuan Li
2025	J	`jnl`	Masked Diffusion Models as Energy Minimization. CoRR Sitong Chen, Shen Nie, Jiacheng Sun, Zijin Feng, Zhenguo Li, Ji-Rong Wen, Chongxuan Li
2025	J	`jnl`	On Memorization in Diffusion Models. Trans. Mach. Learn. Res. Xiangming Gu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Ye Wang
2025	J	`jnl`	Principled RL for Diffusion LLMs Emerges from a Sequence-Level Perspective. CoRR Jingyang Ou, Jiaqi Han, Minkai Xu, Shaoxuan Xu, Jianwen Xie, Stefano Ermon, Yi Wu, Chongxuan Li
2025	A*	`conf`	RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers. ICML Min Zhao, Guande He, Yixiao Chen, Hongzhou Zhu, Chongxuan Li, Jun Zhu
2025	J	`jnl`	RIFLEx: A Free Lunch for Length Extrapolation in Video Diffusion Transformers. CoRR Min Zhao, Guande He, Yixiao Chen, Hongzhou Zhu, Chongxuan Li, Jun Zhu
2025	J	`jnl`	ReFusion: A Diffusion Large Language Model with Parallel Autoregressive Decoding. CoRR Jia-Nan Li, Jian Guan, Wei Wu, Chongxuan Li
2025	J	`jnl`	Reinforcing General Reasoning without Verifiers. CoRR Xiangxin Zhou, Zichen Liu, Anya Sims, Haonan Wang, Tianyu Pang, Chongxuan Li, Liang Wang, Min Lin, Chao Du
2025	J	`jnl`	Saying the Unsaid: Revealing the Hidden Language of Multimodal Systems Through Telephone Games. CoRR Juntu Zhao, Jialing Zhang, Chongxuan Li, Dequan Wang
2025	J	`jnl`	Scaling Diffusion Transformers Efficiently via μP. CoRR Chenyu Zheng, Xinyu Zhang, Rongzhen Wang, Wei Huang, Zhi Tian, Weilin Huang, Jun Zhu, Chongxuan Li
2025	A*	`conf`	Scaling up Masked Diffusion Models on Text. ICLR Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu, Guangtao Zeng, Min Lin, Chongxuan Li
2025	J	`jnl`	UltraImage: Rethinking Resolution Extrapolation in Image Diffusion Transformers. CoRR Min Zhao, Bokai Yan, Xue Yang, Hongzhou Zhu, Jintao Zhang, Shilong Liu, Chongxuan Li, Jun Zhu
2025	J	`jnl`	UltraLLaDA: Scaling the Context Length to 128K for Diffusion Large Language Models. CoRR Guangxin He, Shen Nie, Fengqi Zhu, Yuankang Zhao, Tianyi Bai, Ran Yan, Jie Fu, Chongxuan Li, Binhang Yuan
2025	J	`jnl`	UltraViCo: Breaking Extrapolation Limits in Video Diffusion Transformers. CoRR Min Zhao, Hongzhou Zhu, Yingze Wang, Bokai Yan, Jintao Zhang, Guande He, Ling Yang, Chongxuan Li, Jun Zhu
2025	J	`jnl`	Variational Reasoning for Language Models. CoRR Xiangxin Zhou, Zichen Liu, Haonan Wang, Chao Du, Min Lin, Chongxuan Li, Liang Wang, Tianyu Pang
2025	A*	`conf`	Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data. ICLR Jingyang Ou, Shen Nie, Kaiwen Xue, Fengqi Zhu, Jiacheng Sun, Zhenguo Li, Chongxuan Li
2024	J	`jnl`	Are Image Distributions Indistinguishable to Humans Indistinguishable to Classifiers? CoRR Zebin You, Xinyu Zhang, Hanzhong Guo, Jingdong Wang, Chongxuan Li
2024	A*	`conf`	BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. ICLR Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
2024	—	`conf`	CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model. ECCV (31) Zhengyi Wang, Yikai Wang, Yifei Chen, Chendong Xiang, Shuo Chen, Dajiang Yu, Chongxuan Li, Hang Su, Jun Zhu
2024	J	`jnl`	CRM: Single Image to 3D Textured Mesh with Convolutional Reconstruction Model. CoRR Zhengyi Wang, Yikai Wang, Yifei Chen, Chendong Xiang, Shuo Chen, Dajiang Yu, Chongxuan Li, Hang Su, Jun Zhu
2024	A*	`conf`	EquiPocket: an E(3)-Equivariant Geometric Graph Neural Network for Ligand Binding Site Prediction. ICML Yang Zhang, Zhewei Wei, Ye Yuan, Chongxuan Li, Wenbing Huang
2024	A*	`conf`	Graph Diffusion Policy Optimization. NeurIPS Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Wei Chen
2024	J	`jnl`	Graph Diffusion Policy Optimization. CoRR Yijing Liu, Chao Du, Tianyu Pang, Chongxuan Li, Wei Chen, Min Lin
2024	—	`conf`	HierAffinity: Predicting Protein-Ligand Binding Affinity With Hierarchical Modeling. DASFAA (7) Yang Zhang, Zhewei Wei, Wenbing Huang, Chongxuan Li
2024	A*	`conf`	Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model. NeurIPS Min Zhao, Hongzhou Zhu, Chendong Xiang, Kaiwen Zheng, Chongxuan Li, Jun Zhu
2024	J	`jnl`	Identifying and Solving Conditional Image Leakage in Image-to-Video Diffusion Model. CoRR Min Zhao, Hongzhou Zhu, Chendong Xiang, Kaiwen Zheng, Chongxuan Li, Jun Zhu
2024	J	`jnl`	Improving Long-Text Alignment for Text-to-Image Diffusion Models. CoRR Luping Liu, Chao Du, Tianyu Pang, Zehan Wang, Chongxuan Li, Dong Xu
2024	—	`conf`	Lost in Translation: Latent Concept Misalignment in Text-to-Image Diffusion Models. ECCV (69) Juntu Zhao, Junyu Deng, Yixin Ye, Chongxuan Li, Zhijie Deng, Dequan Wang
2024	J	`jnl`	Lost in Translation: Latent Concept Misalignment in Text-to-Image Diffusion Models. CoRR Juntu Zhao, Junyu Deng, Yixin Ye, Chongxuan Li, Zhijie Deng, Dequan Wang
2024	A*	`conf`	Lower Bounds of Uniform Stability in Gradient-Based Bilevel Algorithms for Hyperparameter Optimization. NeurIPS Rongzhen Wang, Chenyu Zheng, Guoqiang Wu, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
2024	J	`jnl`	MicroDreamer: Zero-shot 3D Generation in ~20 Seconds by Score-based Iterative Reconstruction. CoRR Luxi Chen, Zhengyi Wang, Chongxuan Li, Tingting Gao, Hang Su, Jun Zhu
2024	A*	`conf`	On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability. NeurIPS Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li
2024	J	`jnl`	On Mesa-Optimization in Autoregressively Trained Transformers: Emergence and Capability. CoRR Chenyu Zheng, Wei Huang, Rongzhen Wang, Guoqiang Wu, Jun Zhu, Chongxuan Li
2024	—	`conf`	PoseCrafter: One-Shot Personalized Video Synthesis Following Flexible Pose Control. ECCV (44) Yong Zhong, Min Zhao, Zebin You, Xiaofeng Yu, Changwang Zhang, Chongxuan Li
2024	J	`jnl`	PoseCrafter: One-Shot Personalized Video Synthesis Following Flexible Pose Control. CoRR Yong Zhong, Min Zhao, Zebin You, Xiaofeng Yu, Changwang Zhang, Chongxuan Li
2024	J	`jnl`	Probabilistic Neural-Symbolic Models With Inductive Posterior Constraints. IEEE Trans. Neural Networks Learn. Syst. Ke Su, Hang Su, Chongxuan Li, Jun Zhu, Bo Zhang
2024	Misc	`conf`	Progressive Image Synthesis from Semantics to Details with Denoising Diffusion GAN. ICASSP Guoxing Yang, Haoyu Lu, Chongxuan Li, Guang Zhou, Haoran Wu, Zhiwu Lu
2024	J	`jnl`	Real-time Identity Defenses against Malicious Personalization of Diffusion Models. CoRR Hanzhong Guo, Shen Nie, Chao Du, Tianyu Pang, Hao Sun, Chongxuan Li
2024	J	`jnl`	Scaling up Masked Diffusion Models on Text. CoRR Shen Nie, Fengqi Zhu, Chao Du, Tianyu Pang, Qian Liu, Guangtao Zeng, Min Lin, Chongxuan Li
2024	—	`conf`	Solving Inverse Problem with Unspecified Forward Operator Using Diffusion Models. ECCV Workshops (9) Jialing Zhang, Chongxuan Li, Dequan Wang
2024	A*	`conf`	The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing. ICLR Shen Nie, Hanzhong Allan Guo, Cheng Lu, Yuhao Zhou, Chenyu Zheng, Chongxuan Li
2024	—	`conf`	TransPocket: Structural and Geometric Transformer for Ligand Binding Site Detection. DASFAA (7) Yang Zhang, Zhewei Wei, Wenbing Huang, Chongxuan Li
2024	A*	`conf`	Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. ICML Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
2024	J	`jnl`	Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential Equations. CoRR Kaiwen Xue, Yuhao Zhou, Shen Nie, Xu Min, Xiaolu Zhang, Jun Zhou, Chongxuan Li
2024	J	`jnl`	Your Absorbing Discrete Diffusion Secretly Models the Conditional Distributions of Clean Data. CoRR Jingyang Ou, Shen Nie, Kaiwen Xue, Fengqi Zhu, Jiacheng Sun, Zhenguo Li, Chongxuan Li
2023	J	`jnl`	A Closer Look at Parameter-Efficient Tuning in Diffusion Models. CoRR Chendong Xiang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu
2023	A*	`conf`	All are Worth Words: A ViT Backbone for Diffusion Models. CVPR Fan Bao, Shen Nie, Kaiwen Xue, Yue Cao, Chongxuan Li, Hang Su, Jun Zhu
2023	J	`jnl`	BayesDiff: Estimating Pixel-wise Uncertainty in Diffusion via Bayesian Inference. CoRR Siqi Kou, Lei Gan, Dequan Wang, Chongxuan Li, Zhijie Deng
2023	A*	`conf`	Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. ICML Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu
2023	J	`jnl`	Contrastive Energy Prediction for Exact Energy-Guided Diffusion Sampling in Offline Reinforcement Learning. CoRR Cheng Lu, Huayu Chen, Jianfei Chen, Hang Su, Chongxuan Li, Jun Zhu
2023	J	`jnl`	ControlVideo: Adding Conditional Control for One Shot Text-to-Video Editing. CoRR Min Zhao, Rongzhen Wang, Fan Bao, Chongxuan Li, Jun Zhu
2023	A*	`conf`	Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models. ICLR Yong Zhong, Hongtao Liu, Xiaodong Liu, Fan Bao, Weiran Shen, Chongxuan Li
2023	A*	`conf`	Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. NeurIPS Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu
2023	J	`jnl`	Diffusion Models and Semi-Supervised Learners Benefit Mutually with Few Labels. CoRR Zebin You, Yong Zhong, Fan Bao, Jiacheng Sun, Chongxuan Li, Jun Zhu
2023	A*	`conf`	Equivariant Energy-Guided SDE for Inverse Molecular Design. ICLR Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
2023	A*	`conf`	Gaussian Mixture Solvers for Diffusion Models. NeurIPS Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li
2023	J	`jnl`	Gaussian Mixture Solvers for Diffusion Models. CoRR Hanzhong Guo, Cheng Lu, Fan Bao, Tianyu Pang, Shuicheng Yan, Chao Du, Chongxuan Li
2023	J	`jnl`	Inversion-by-Inversion: Exemplar-based Sketch-to-Photo Synthesis via Stochastic Differential Equations without Training. CoRR Ximing Xing, Chuang Wang, Haitao Zhou, Zhihao Hu, Chongxuan Li, Dong Xu, Qian Yu
2023	J	`jnl`	MissDiff: Training Diffusion Models on Tabular Data with Missing Values. CoRR Yidong Ouyang, Liyan Xie, Chongxuan Li, Guang Cheng
2023	A*	`conf`	On Evaluating Adversarial Robustness of Large Vision-Language Models. NeurIPS Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin
2023	J	`jnl`	On Evaluating Adversarial Robustness of Large Vision-Language Models. CoRR Yunqing Zhao, Tianyu Pang, Chao Du, Xiao Yang, Chongxuan Li, Ngai-Man Cheung, Min Lin
2023	J	`jnl`	On Memorization in Diffusion Models. CoRR Xiangming Gu, Chao Du, Tianyu Pang, Chongxuan Li, Min Lin, Ye Wang
2023	A*	`conf`	One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. ICML Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, Jun Zhu
2023	J	`jnl`	One Transformer Fits All Distributions in Multi-Modal Diffusion at Scale. CoRR Fan Bao, Shen Nie, Kaiwen Xue, Chongxuan Li, Shi Pu, Yaole Wang, Gang Yue, Yue Cao, Hang Su, Jun Zhu
2023	A*	`conf`	ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation. NeurIPS Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu
2023	J	`jnl`	ProlificDreamer: High-Fidelity and Diverse Text-to-3D Generation with Variational Score Distillation. CoRR Zhengyi Wang, Cheng Lu, Yikai Wang, Fan Bao, Chongxuan Li, Hang Su, Jun Zhu
2023	A*	`conf`	Revisiting Discriminative vs. Generative Classifiers: Theory and Implications. ICML Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu
2023	J	`jnl`	Revisiting Discriminative vs. Generative Classifiers: Theory and Implications. CoRR Chenyu Zheng, Guoqiang Wu, Fan Bao, Yue Cao, Chongxuan Li, Jun Zhu
2023	J	`jnl`	The Blessing of Randomness: SDE Beats ODE in General Diffusion-based Image Editing. CoRR Shen Nie, Hanzhong Allan Guo, Cheng Lu, Yuhao Zhou, Chenyu Zheng, Chongxuan Li
2023	A*	`conf`	Toward Understanding Generative Data Augmentation. NeurIPS Chenyu Zheng, Guoqiang Wu, Chongxuan Li
2023	J	`jnl`	Toward Understanding Generative Data Augmentation. CoRR Chenyu Zheng, Guoqiang Wu, Chongxuan Li
2023	A*	`conf`	Towards Understanding Generalization of Macro-AUC in Multi-label Learning. ICML Guoqiang Wu, Chongxuan Li, Yilong Yin
2023	J	`jnl`	Towards Understanding Generalization of Macro-AUC in Multi-label Learning. CoRR Guoqiang Wu, Chongxuan Li, Yilong Yin
2023	J	`jnl`	Uncertainty quantification via a memristor Bayesian deep neural network for risk-sensitive reinforcement learning. Nat. Mac. Intell. Yudeng Lin, Qingtian Zhang, Bin Gao, Jianshi Tang, Peng Yao, Chongxuan Li, Shiyu Huang, Zhengwu Liu, Ying Zhou, Yuyi Liu, Wenqiang Zhang, Jun Zhu, He Qian, Huaqiang Wu
2022	J	`jnl`	All are Worth Words: a ViT Backbone for Score-based Diffusion Models. CoRR Fan Bao, Chongxuan Li, Yue Cao, Jun Zhu
2022	A*	`conf`	Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. ICLR Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
2022	J	`jnl`	Analytic-DPM: an Analytic Estimate of the Optimal Reverse Variance in Diffusion Probabilistic Models. CoRR Fan Bao, Chongxuan Li, Jun Zhu, Bo Zhang
2022	J	`jnl`	DPM-Solver++: Fast Solver for Guided Sampling of Diffusion Probabilistic Models. CoRR Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
2022	A*	`conf`	DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. NeurIPS Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
2022	J	`jnl`	DPM-Solver: A Fast ODE Solver for Diffusion Probabilistic Model Sampling in Around 10 Steps. CoRR Cheng Lu, Yuhao Zhou, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
2022	J	`jnl`	Deep Generative Modeling on Limited Data with Regularization by Nontransferable Pre-trained Models. CoRR Yong Zhong, Hongtao Liu, Xiaodong Liu, Fan Bao, Weiran Shen, Chongxuan Li
2022	J	`jnl`	Deep reinforcement learning with credit assignment for combinatorial optimization. Pattern Recognit. Dong Yan, Jiayi Weng, Shiyu Huang, Chongxuan Li, Yichi Zhou, Hang Su, Jun Zhu
2022	A*	`conf`	EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. NeurIPS Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu
2022	J	`jnl`	EGSDE: Unpaired Image-to-Image Translation via Energy-Guided Stochastic Differential Equations. CoRR Min Zhao, Fan Bao, Chongxuan Li, Jun Zhu
2022	J	`jnl`	Equivariant Energy-Guided SDE for Inverse Molecular Design. CoRR Fan Bao, Min Zhao, Zhongkai Hao, Peiyao Li, Chongxuan Li, Jun Zhu
2022	A*	`conf`	Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models. ICML Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang
2022	J	`jnl`	Estimating the Optimal Covariance with Imperfect Mean in Diffusion Probabilistic Models. CoRR Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu, Bo Zhang
2022	A*	`conf`	Fast Lossless Neural Compression with Integer-Only Discrete Flows. ICML Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang
2022	J	`jnl`	Fast Lossless Neural Compression with Integer-Only Discrete Flows. CoRR Siyu Wang, Jianfei Chen, Chongxuan Li, Jun Zhu, Bo Zhang
2022	J	`jnl`	Maximum Likelihood Training for Score-Based Diffusion ODEs by High-Order Denoising Score Matching. CoRR Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
2022	A*	`conf`	Maximum Likelihood Training for Score-based Diffusion ODEs by High Order Denoising Score Matching. ICML Cheng Lu, Kaiwen Zheng, Fan Bao, Jianfei Chen, Chongxuan Li, Jun Zhu
2022	A*	`conf`	Memory Replay with Data Compression for Continual Learning. ICLR Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu
2022	J	`jnl`	Memory Replay with Data Compression for Continual Learning. CoRR Liyuan Wang, Xingxing Zhang, Kuo Yang, Longhui Yu, Chongxuan Li, Lanqing Hong, Shifeng Zhang, Zhenguo Li, Yi Zhong, Jun Zhu
2022	J	`jnl`	Triple Generative Adversarial Networks. IEEE Trans. Pattern Anal. Mach. Intell. Chongxuan Li, Kun Xu, Jun Zhu, Jiashuo Liu, Bo Zhang
2022	J	`jnl`	Why Are Conditional Generative Models Better Than Unconditional Ones? CoRR Fan Bao, Chongxuan Li, Jiacheng Sun, Jun Zhu
2021	A*	`conf`	Implicit Normalizing Flows. ICLR Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
2021	J	`jnl`	Implicit Normalizing Flows. CoRR Cheng Lu, Jianfei Chen, Chongxuan Li, Qiuhao Wang, Jun Zhu
2021	A*	`conf`	MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering. ICLR Tsung Wei Tsai, Chongxuan Li, Jun Zhu
2021	J	`jnl`	MiCE: Mixture of Contrastive Experts for Unsupervised Image Clustering. CoRR Tsung Wei Tsai, Chongxuan Li, Jun Zhu
2021	A*	`conf`	ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-Supervised Continual Learning. CVPR Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu
2021	J	`jnl`	ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning. CoRR Liyuan Wang, Kuo Yang, Chongxuan Li, Lanqing Hong, Zhenguo Li, Jun Zhu
2021	J	`jnl`	Relaxed Conditional Image Transfer for Semi-supervised Domain Adaptation. CoRR Qijun Luo, Zhili Liu, Lanqing Hong, Chongxuan Li, Kuo Yang, Liyuan Wang, Fengwei Zhou, Guilin Li, Zhenguo Li, Jun Zhu
2021	A*	`conf`	Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. NeurIPS Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu
2021	J	`jnl`	Rethinking and Reweighting the Univariate Losses for Multi-Label Ranking: Consistency and Generalization. CoRR Guoqiang Wu, Chongxuan Li, Kun Xu, Jun Zhu
2021	A*	`conf`	Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. NeurIPS Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang
2021	J	`jnl`	Stability and Generalization of Bilevel Programming in Hyperparameter Optimization. CoRR Fan Bao, Guoqiang Wu, Chongxuan Li, Jun Zhu, Bo Zhang
2021	A*	`conf`	Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. ICML Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
2020	A*	`conf`	Bi-level Score Matching for Learning Energy-based Latent Variable Models. NeurIPS Fan Bao, Chongxuan Li, Taufik Xu, Hang Su, Jun Zhu, Bo Zhang
2020	J	`jnl`	Bi-level Score Matching for Learning Energy-based Latent Variable Models. CoRR Fan Bao, Chongxuan Li, Kun Xu, Hang Su, Jun Zhu, Bo Zhang
2020	A*	`conf`	Efficient Learning of Generative Models via Finite-Difference Score Matching. NeurIPS Tianyu Pang, Taufik Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu
2020	J	`jnl`	Efficient Learning of Generative Models via Finite-Difference Score Matching. CoRR Tianyu Pang, Kun Xu, Chongxuan Li, Yang Song, Stefano Ermon, Jun Zhu
2020	—	`conf`	Learning Implicit Generative Models by Teaching Density Estimators. ECML/PKDD (2) Kun Xu, Chao Du, Chongxuan Li, Jun Zhu, Bo Zhang
2020	A*	`conf`	To Relieve Your Headache of Training an MRF, Take AdVIL. ICLR Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang
2020	A*	`conf`	Understanding and Stabilizing GANs' Training Dynamics Using Control Theory. ICML Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang
2020	J	`jnl`	Variational (Gradient) Estimate of the Score Function in Energy-based Latent Variable Models. CoRR Fan Bao, Kun Xu, Chongxuan Li, Lanqing Hong, Jun Zhu, Bo Zhang
2019	J	`jnl`	Adversarial Variational Inference and Learning in Markov Random Fields. CoRR Chongxuan Li, Chao Du, Kun Xu, Max Welling, Jun Zhu, Bo Zhang
2019	J	`jnl`	DS CoRR Tsung Wei Tsai, Chongxuan Li, Jun Zhu
2019	A*	`conf`	Multi-objects Generation with Amortized Structural Regularization. NeurIPS Taufik Xu, Chongxuan Li, Jun Zhu, Bo Zhang
2019	J	`jnl`	Multi-objects Generation with Amortized Structural Regularization. CoRR Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang
2019	J	`jnl`	Triple Generative Adversarial Networks. CoRR Chongxuan Li, Kun Xu, Jiashuo Liu, Jun Zhu, Bo Zhang
2019	J	`jnl`	Understanding and Stabilizing GANs' Training Dynamics with Control Theory. CoRR Kun Xu, Chongxuan Li, Huanshu Wei, Jun Zhu, Bo Zhang
2018	A*	`conf`	Collaborative Filtering With User-Item Co-Autoregressive Models. AAAI Chao Du, Chongxuan Li, Yin Zheng, Jun Zhu, Bo Zhang
2018	A*	`conf`	Graphical Generative Adversarial Networks. NeurIPS Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang
2018	J	`jnl`	Graphical Generative Adversarial Networks. CoRR Chongxuan Li, Max Welling, Jun Zhu, Bo Zhang
2018	J	`jnl`	Learning Implicit Generative Models by Teaching Explicit Ones. CoRR Chao Du, Kun Xu, Chongxuan Li, Jun Zhu, Bo Zhang
2018	A*	`conf`	Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. IJCAI Danyang Sun, Tongzheng Ren, Chongxuan Li, Hang Su, Jun Zhu
2018	J	`jnl`	Max-Margin Deep Generative Models for (Semi-)Supervised Learning. IEEE Trans. Pattern Anal. Mach. Intell. Chongxuan Li, Jun Zhu, Bo Zhang
2017	J	`jnl`	Learning to Write Stylized Chinese Characters by Reading a Handful of Examples. CoRR Danyang Sun, Tongzheng Ren, Chongxuan Li, Jun Zhu, Hang Su
2017	—	`conf`	Population Matching Discrepancy and Applications in Deep Learning. NIPS Jianfei Chen, Chongxuan Li, Yizhong Ru, Jun Zhu
2017	J	`jnl`	Towards Better Analysis of Deep Convolutional Neural Networks. IEEE Trans. Vis. Comput. Graph. Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu
2017	—	`conf`	Triple Generative Adversarial Nets. NIPS Chongxuan Li, Taufik Xu, Jun Zhu, Bo Zhang
2017	J	`jnl`	Triple Generative Adversarial Nets. CoRR Chongxuan Li, Kun Xu, Jun Zhu, Bo Zhang
2016	J	`jnl`	Collaborative Filtering with User-Item Co-Autoregressive Models. CoRR Chao Du, Chongxuan Li, Yin Zheng, Jun Zhu, Cailiang Liu, Hanning Zhou, Bo Zhang
2016	A*	`conf`	Learning to Generate with Memory. ICML Chongxuan Li, Jun Zhu, Bo Zhang
2016	J	`jnl`	Learning to Generate with Memory. CoRR Chongxuan Li, Jun Zhu, Bo Zhang
2016	J	`jnl`	Max-Margin Deep Generative Models for (Semi-)Supervised Learning. CoRR Chongxuan Li, Jun Zhu, Bo Zhang
2016	J	`jnl`	Towards Better Analysis of Deep Convolutional Neural Networks. CoRR Mengchen Liu, Jiaxin Shi, Zhen Li, Chongxuan Li, Jun Zhu, Shixia Liu
2015	—	`conf`	Max-Margin Deep Generative Models. NIPS Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang
2015	J	`jnl`	Max-margin Deep Generative Models. CoRR Chongxuan Li, Jun Zhu, Tianlin Shi, Bo Zhang