Zhendong Wang

According to our database, Zhendong Wang authored at least 29 papers between 2020 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Distilled Protein Backbone Generation.

Liyang Xie, Haoran Zhang, Zhendong Wang, Wesley Tansey, Mingyuan Zhou

CoRR, October, 2025

EdiVal-Agent: An Object-Centric Framework for Automated, Scalable, Fine-Grained Evaluation of Multi-Turn Editing.

Tianyu Chen, Yasi Zhang, Zhi Zhang, Peiyu Yu, Shu Wang, Zhendong Wang, Kevin Lin, Xiaofei Wang, Zhengyuan Yang, Linjie Li, Chung-Ching Lin, Jianwen Xie, Oscar Leong, Lijuan Wang, Ying Nian Wu, Mingyuan Zhou

CoRR, September, 2025

Improving Data Efficiency for LLM Reinforcement Fine-tuning Through Difficulty-targeted Online Data Selection and Rollout Replay.

Yifan Sun, Jingyan Shen, Yibin Wang, Tianyu Chen, Zhendong Wang, Mingyuan Zhou, Huan Zhang

CoRR, June, 2025

Restoration Score Distillation: From Corrupted Diffusion Pretraining to One-Step High-Quality Generation.

Yasi Zhang, Tianyu Chen, Zhendong Wang, Ying Nian Wu, Mingyuan Zhou, Oscar Leong

CoRR, May, 2025

Few-Step Diffusion via Score identity Distillation.

Mingyuan Zhou, Yi Gu, Zhendong Wang

CoRR, May, 2025

Denoising Score Distillation: From Noisy Diffusion Pretraining to One-Step High-Quality Generation.

Tianyu Chen, Yasi Zhang, Zhendong Wang, Ying Nian Wu, Oscar Leong, Mingyuan Zhou

CoRR, March, 2025

Adversarial Score identity Distillation: Rapidly Surpassing the Teacher in One Step.

Mingyuan Zhou, Huangjie Zheng, Yi Gu, Zhendong Wang, Hai Huang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation.

Mingyuan Zhou, Zhendong Wang, Huangjie Zheng, Hai Huang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

2024

Enhancing and Accelerating Diffusion-Based Inverse Problem Solving through Measurements Optimization.

Tianyu Chen, Zhendong Wang, Mingyuan Zhou

CoRR, 2024

One-Step Diffusion Policy: Fast Visuomotor Policies via Diffusion Distillation.

Zhendong Wang, Zhaoshuo Li, Ajay Mandlekar, Zhenjia Xu, Jiaojiao Fan, Yashraj Narang, Linxi Fan, Yuke Zhu, Yogesh Balaji, Mingyuan Zhou, Ming-Yu Liu, Yu Zeng

CoRR, 2024

Diffusion-RPO: Aligning Diffusion Models through Relative Preference Optimization.

Yi Gu, Zhendong Wang, Yueqin Yin, Yujia Xie, Mingyuan Zhou

CoRR, 2024

Long and Short Guidance in Score identity Distillation for One-Step Text-to-Image Generation.

Mingyuan Zhou, Zhendong Wang, Huangjie Zheng, Hai Huang

CoRR, 2024

Self-Augmented Preference Optimization: Off-Policy Paradigms for Language Model Alignment.

Yueqin Yin, Zhendong Wang, Yujia Xie, Weizhu Chen, Mingyuan Zhou

CoRR, 2024

Take the Bull by the Horns: Hard Sample-Reweighted Continual Training Improves LLM Generalization.

Xuxi Chen, Zhendong Wang, Daouda Sow, Junjie Yang, Tianlong Chen, Yingbin Liang, Mingyuan Zhou, Zhangyang Wang

CoRR, 2024

Relative Preference Optimization: Enhancing LLM Alignment through Contrasting Responses across Identical and Diverse Prompts.

Yueqin Yin, Zhendong Wang, Yi Gu, Hai Huang, Weizhu Chen, Mingyuan Zhou

CoRR, 2024

Diffusion Policies Creating a Trust Region for Offline Reinforcement Learning.

Tianyu Chen, Zhendong Wang, Mingyuan Zhou

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Score identity Distillation: Exponentially Fast Distillation of Pretrained Diffusion Models for One-Step Generation.

Mingyuan Zhou, Huangjie Zheng, Zhendong Wang, Mingzhang Yin, Hai Huang

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Learning Stackable and Skippable LEGO Bricks for Efficient, Reconfigurable, and Variable-Resolution Diffusion Modeling.

Huangjie Zheng, Zhendong Wang, Jianbo Yuan, Guanghan Ning, Pengcheng He, Quanzeng You, Hongxia Yang, Mingyuan Zhou

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Improving In-Context Learning in Diffusion Models with Visual Context-Modulated Prompts.

Tianqi Chen, Yongfei Liu, Zhendong Wang, Jianbo Yuan, Quanzeng You, Hongxia Yang, Mingyuan Zhou

CoRR, 2023

Beta Diffusion.

Mingyuan Zhou, Tianqi Chen, Zhendong Wang, Huangjie Zheng

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models.

Zhendong Wang, Yifan Jiang, Huangjie Zheng, Peihao Wang, Pengcheng He, Zhangyang Wang, Weizhu Chen, Mingyuan Zhou

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

In-Context Learning Unlocked for Diffusion Models.

Zhendong Wang, Yifan Jiang, Yadong Lu, Yelong Shen, Pengcheng He, Weizhu Chen, Zhangyang (Atlas) Wang, Mingyuan Zhou

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Diffusion-GAN: Training GANs with Diffusion.

Zhendong Wang, Huangjie Zheng, Pengcheng He, Weizhu Chen, Mingyuan Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Diffusion Policies as an Expressive Policy Class for Offline Reinforcement Learning.

Zhendong Wang, Jonathan J. Hunt, Mingyuan Zhou

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Probabilistic Conformal Prediction Using Conditional Random Samples.

Zhendong Wang, Ruijiang Gao, Mingzhang Yin, Mingyuan Zhou, David M. Blei

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

A Regularized Implicit Policy for Offline Reinforcement Learning.

Shentao Yang, Zhendong Wang, Huangjie Zheng, Yihao Feng, Mingyuan Zhou

CoRR, 2022

2020

Implicit Distributional Reinforcement Learning.

Yuguang Yue, Zhendong Wang, Mingyuan Zhou

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Thompson Sampling via Local Uncertainty.

Zhendong Wang, Mingyuan Zhou

Proceedings of the 37th International Conference on Machine Learning, 2020

Adaptive Correlated Monte Carlo for Contextual Categorical Sequence Generation.

Xinjie Fan, Yizhe Zhang, Zhendong Wang, Mingyuan Zhou

Proceedings of the 8th International Conference on Learning Representations, 2020