Qinsheng Zhang

55 papers A* 15Journal 38Unranked 1

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Bridging Supervised Learning and Reinforcement Learning in Math Reasoning. CoRR Huayu Chen, Kaiwen Zheng, Qinsheng Zhang, Ganqu Cui, Yin Cui, Haotian Ye, Tsung-Yi Lin, Ming-Yu Liu, Jun Zhu, Haoxiang Wang
2025	J	`jnl`	Cosmos World Foundation Model Platform for Physical AI. CoRR Niket Agarwal, Arslan Ali, Maciej Bala, Yogesh Balaji, Erik Barker, Tiffany Cai, Prithvijit Chattopadhyay, Yongxin Chen, Yin Cui, Yifan Ding, Daniel Dworakowski, Jiaojiao Fan, Michele Fenzi, Francesco Ferroni, Sanja Fidler, Dieter Fox, Songwei Ge, Yunhao Ge, Jinwei Gu, Siddharth Gururani, Ethan He, Jiahui Huang, Jacob Samuel Huffman, Pooya Jannaty, Jingyi Jin, Seung Wook Kim, Gergely Klár, Grace Lam, Shiyi Lan, Laura Leal-Taixé, Anqi Li, Zhaoshuo Li, Chen-Hsuan Lin, Tsung-Yi Lin, Huan Ling, Ming-Yu Liu, Xian Liu, Alice Luo, Qianli Ma, Hanzi Mao, Kaichun Mo, Arsalan Mousavian, Seungjun Nah, Sriharsha Niverty, David Page, Despoina Paschalidou, Zeeshan Patel, Lindsey Pavao, Morteza Ramezanali, Fitsum Reda, Xiaowei Ren, Vasanth Rao Naik Sabavat, Ed Schmerling, Stella Shi, Bartosz Stefaniak, Shitao Tang, Lyne Tchapmi, Przemek Tredak, Wei-Cheng Tseng, Jibin Varghese, Hao Wang, Haoxiang Wang, Heng Wang, Ting-Chun Wang, Fangyin Wei, Xinyue Wei, Jay Zhangjie Wu, Jiashu Xu, Wei Yang, Yen-Chen Lin, Xiaohui Zeng, Yu Zeng, Jing Zhang, Qinsheng Zhang, Yuxuan Zhang, Qingqing Zhao, Artur Zólkowski
2025	J	`jnl`	Data-regularized Reinforcement Learning for Diffusion Models at Scale. CoRR Haotian Ye, Kaiwen Zheng, Jiashu Xu, Puheng Li, Huayu Chen, Jiaqi Han, Sheng Liu, Qinsheng Zhang, Hanzi Mao, Zekun Hao, Prithvijit Chattopadhyay, Dinghao Yang, Liang Feng, Maosheng Liao, Junjie Bai, Ming-Yu Liu, James Zou, Stefano Ermon
2025	J	`jnl`	DiffusionNFT: Online Diffusion Reinforcement with Forward Process. CoRR Kaiwen Zheng, Huayu Chen, Haotian Ye, Haoxiang Wang, Qinsheng Zhang, Kai Jiang, Hang Su, Stefano Ermon, Jun Zhu, Ming-Yu Liu
2025	A*	`conf`	Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator. ICML Kaiwen Zheng, Yongxin Chen, Huayu Chen, Guande He, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang
2025	J	`jnl`	Direct Discriminative Optimization: Your Likelihood-Based Visual Generative Model is Secretly a GAN Discriminator. CoRR Kaiwen Zheng, Yongxin Chen, Huayu Chen, Guande He, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang
2025	A*	`conf`	EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generation. ICLR Jiaxiang Tang, Zhaoshuo Li, Zekun Hao, Xian Liu, Gang Zeng, Ming-Yu Liu, Qinsheng Zhang
2025	J	`jnl`	Generalized Neighborhood Attention: Multi-dimensional Sparse Attention at the Speed of Light. CoRR Ali Hassani, Fengzhe Zhou, Aditya Kane, Jiannan Huang, Chieh-Yun Chen, Min Shi, Steven Walton, Markus Hoehnerbach, Vijay Thakkar, Michael Isaev, Qinsheng Zhang, Bing Xu, Haicheng Wu, Wen-Mei Hwu, Ming-Yu Liu, Humphrey Shi
2025	A*	`conf`	High-Quality Joint Image and Video Tokenization with Causal VAE. ICLR Dawit Mureja Argaw, Xian Liu, Qinsheng Zhang, Joon Son Chung, Ming-Yu Liu, Fitsum Reda
2025	J	`jnl`	Large Scale Diffusion Distillation via Score-Regularized Continuous-Time Consistency. CoRR Kaiwen Zheng, Yuji Wang, Qianli Ma, Huayu Chen, Jintao Zhang, Yogesh Balaji, Jianfei Chen, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang
2025	A*	`conf`	Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling. ICLR Kaiwen Zheng, Yongxin Chen, Hanzi Mao, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang
2025	J	`jnl`	Scalable Policy Evaluation with Video World Models. CoRR Wei-Cheng Tseng, Jinwei Gu, Qinsheng Zhang, Hanzi Mao, Ming-Yu Liu, Florian Shkurti, Lin Yen-Chen
2024	J	`jnl`	A parallel framework for graphical optimal transport. CoRR Jiaojiao Fan, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2024	A*	`conf`	Condition-Aware Neural Network for Controlled Image Generation. CVPR Han Cai, Muyang Li, Qinsheng Zhang, Ming-Yu Liu, Song Han
2024	J	`jnl`	Condition-Aware Neural Network for Controlled Image Generation. CoRR Han Cai, Muyang Li, Zhuoyang Zhang, Qinsheng Zhang, Ming-Yu Liu, Song Han
2024	A*	`conf`	DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models. CVPR Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Kai Li, Song Han
2024	J	`jnl`	DistriFusion: Distributed Parallel Inference for High-Resolution Diffusion Models. CoRR Muyang Li, Tianle Cai, Jiaxin Cao, Qinsheng Zhang, Han Cai, Junjie Bai, Yangqing Jia, Ming-Yu Liu, Kai Li, Song Han
2024	J	`jnl`	EdgeRunner: Auto-regressive Auto-encoder for Artistic Mesh Generation. CoRR Jiaxiang Tang, Zhaoshuo Li, Zekun Hao, Xian Liu, Gang Zeng, Ming-Yu Liu, Qinsheng Zhang
2024	J	`jnl`	Edify 3D: Scalable High-Quality 3D Asset Generation. CoRR Maciej Bala, Yin Cui, Yifan Ding, Yunhao Ge, Zekun Hao, Jon Hasselgren, Jacob Samuel Huffman, Jingyi Jin, J. P. Lewis, Zhaoshuo Li, Chen-Hsuan Lin, Yen-Chen Lin, Tsung-Yi Lin, Ming-Yu Liu, Alice Luo, Qianli Ma, Jacob Munkberg, Stella Shi, Fangyin Wei, Donglai Xiang, Jiashu Xu, Xiaohui Zeng, Qinsheng Zhang
2024	J	`jnl`	Edify Image: High-Quality Image Generation with Pixel Space Laplacian Diffusion Models. CoRR Yuval Atzmon, Maciej Bala, Yogesh Balaji, Tiffany Cai, Yin Cui, Jiaojiao Fan, Yunhao Ge, Siddharth Gururani, Jacob Samuel Huffman, Ronald Isaac, Pooya Jannaty, Tero Karras, Grace Lam, J. P. Lewis, Aaron Licata, Yen-Chen Lin, Ming-Yu Liu, Qianli Ma, Arun Mallya, Ashlee Martino-Tarr, Doug Mendez, Seungjun Nah, Chris Pruett, Fitsum Reda, Jiaming Song, Ting-Chun Wang, Fangyin Wei, Xiaohui Zeng, Yu Zeng, Qinsheng Zhang
2024	—	`—`	Learning, sampling and inference with stochastic differential equations. Qinsheng Zhang
2024	J	`jnl`	Masked Diffusion Models are Secretly Time-Agnostic Masked Models and Exploit Inaccurate Categorical Sampling. CoRR Kaiwen Zheng, Yongxin Chen, Hanzi Mao, Ming-Yu Liu, Jun Zhu, Qinsheng Zhang
2024	A*	`conf`	RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance. NeurIPS Jiaojiao Fan, Haotian Xue, Qinsheng Zhang, Yongxin Chen
2024	J	`jnl`	RefDrop: Controllable Consistency in Image or Video Generation via Reference Feature Guidance. CoRR Jiaojiao Fan, Haotian Xue, Qinsheng Zhang, Yongxin Chen
2024	A*	`conf`	Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion. ICML Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue
2024	J	`jnl`	Symbolic Music Generation with Non-Differentiable Rule Guided Diffusion. CoRR Yujia Huang, Adishree Ghatare, Yuanzhe Liu, Ziniu Hu, Qinsheng Zhang, Chandramouli Shama Sastry, Siddharth Gururani, Sageev Oore, Yisong Yue
2023	J	`jnl`	An Optimal Control Approach to Particle Filtering on Lie Groups. IEEE Control. Syst. Lett. Bo Yuan, Qinsheng Zhang, Yongxin Chen
2023	J	`jnl`	An optimal control approach to particle filtering. Autom. Qinsheng Zhang, Amirhossein Taghvaei, Yongxin Chen
2023	A*	`conf`	DiffCollage: Parallel Generation of Large Content with Diffusion Models. CVPR Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, Ming-Yu Liu
2023	J	`jnl`	DiffCollage: Parallel Generation of Large Content with Diffusion Models. CoRR Qinsheng Zhang, Jiaming Song, Xun Huang, Yongxin Chen, Ming-Yu Liu
2023	A*	`conf`	Fast Sampling of Diffusion Models with Exponential Integrator. ICLR Qinsheng Zhang, Yongxin Chen
2023	J	`jnl`	Improved Order Analysis and Design of Exponential Integrator for Diffusion Models Sampling. CoRR Qinsheng Zhang, Jiaming Song, Yongxin Chen
2023	A*	`conf`	Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation. ICML Jiaming Song, Qinsheng Zhang, Hongxu Yin, Morteza Mardani, Ming-Yu Liu, Jan Kautz, Yongxin Chen, Arash Vahdat
2023	A*	`conf`	gDDIM: Generalized denoising diffusion implicit models. ICLR Qinsheng Zhang, Molei Tao, Yongxin Chen
2022	J	`jnl`	Fast Sampling of Diffusion Models with Exponential Integrator. CoRR Qinsheng Zhang, Yongxin Chen
2022	J	`jnl`	Inference With Aggregate Data in Probabilistic Graphical Models: An Optimal Transport Approach. IEEE Trans. Autom. Control. Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2022	J	`jnl`	Inference of Aggregate Hidden Markov Models With Continuous Observations. IEEE Control. Syst. Lett. Qinsheng Zhang, Rahul Singh, Yongxin Chen
2022	J	`jnl`	Learning hidden Markov models from aggregate observations. Autom. Rahul Singh, Qinsheng Zhang, Yongxin Chen
2022	A*	`conf`	Path Integral Sampler: A Stochastic Control Approach For Sampling. ICLR Qinsheng Zhang, Yongxin Chen
2022	A*	`conf`	Variational Wasserstein gradient flow. ICML Jiaojiao Fan, Qinsheng Zhang, Amirhossein Taghvaei, Yongxin Chen
2022	J	`jnl`	gDDIM: Generalized denoising diffusion implicit models. CoRR Qinsheng Zhang, Molei Tao, Yongxin Chen
2021	J	`jnl`	An optimal control approach to particle filtering. CoRR Qinsheng Zhang, Amirhossein Taghvaei, Yongxin Chen
2021	A*	`conf`	Diffusion Normalizing Flow. NeurIPS Qinsheng Zhang, Yongxin Chen
2021	J	`jnl`	Diffusion Normalizing Flow. CoRR Qinsheng Zhang, Yongxin Chen
2021	J	`jnl`	Incremental Inference of Collective Graphical Models. IEEE Control. Syst. Lett. Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2021	J	`jnl`	Multi-Marginal Optimal Transport and Probabilistic Graphical Models. IEEE Trans. Inf. Theory Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2021	J	`jnl`	Path Integral Sampler: a stochastic control approach for sampling. CoRR Qinsheng Zhang, Yongxin Chen
2020	J	`jnl`	Filtering for Aggregate Hidden Markov Models with Continuous Observations. CoRR Qinsheng Zhang, Rahul Singh, Yongxin Chen
2020	—	`conf`	Improving Robustness via Risk Averse Distributional Reinforcement Learning. L4DC Rahul Singh, Qinsheng Zhang, Yongxin Chen
2020	J	`jnl`	Improving Robustness via Risk Averse Distributional Reinforcement Learning. CoRR Rahul Singh, Qinsheng Zhang, Yongxin Chen
2020	J	`jnl`	Incremental inference of collective graphical models. CoRR Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2020	J	`jnl`	Inference with Aggregate Data: An Optimal Transport Approach. CoRR Rahul Singh, Isabel Haasler, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2020	J	`jnl`	Learning Hidden Markov Models from Aggregate Observations. CoRR Rahul Singh, Qinsheng Zhang, Yongxin Chen
2020	J	`jnl`	Multi-marginal optimal transport and probabilistic graphical models. CoRR Isabel Haasler, Rahul Singh, Qinsheng Zhang, Johan Karlsson, Yongxin Chen
2014	J	`jnl`	The Effect of Trust on Customers' Online Repurchase Intention in Consumer-to-Consumer Electronic Commerce. J. Organ. End User Comput. Lin Jia, Casey G. Cegielski, Qinsheng Zhang