Publications

* denotes equal contribution. See also my Google Scholar.

Preprints

1. Acceleration of Diffusion Language Model through Discrete Average Generator
   Yidong Ouyang, Zhengyan Wan, Themis Haris, Tian Tan, Liqian Peng, Henry Li, Ziqian Lin, Jianhang Chen, Maryam Karimzadehgan, Alec Go, George Michailidis
   [arxiv]

2. Iterative Exact Discrete Guidance for Energy-Based Sampling
   Yuwen Qian, Yidong Ouyang, Zhengyan Wan, Hongyuan Zha
   [arxiv]

3. LEDFlow: Introducing Entropy-guided Generation Order into Uniform Discrete Flow
   Tung Sum Thomas Kwok, Yidong Ouyang, Yingjia Wan, Ying Nian Wu, Zhijiang Guo, Oscar Leong
   [arxiv]

4. Reinforcing the Generation Order of Multimodal Diffusion Language Models
   Yidong Ouyang, Zhe Wang, Sourav Bhabesh, Dmitriy Bespalov
   [arxiv]

5. dFlowGRPO: Rate-Aware Policy Optimization for Discrete Flow Models
   Zhengyan Wan, Yidong Ouyang, Panwen Hu, Qiang Sun
   [arxiv] [code]

6. Training-Free Self-Correction for Multimodal Masked Diffusion Models
   Yidong Ouyang, Panwen Hu, Zhengyan Wan, Zhe Wang, Liyan Xie, Dmitriy Bespalov, Ying Nian Wu, Guang Cheng, Hongyuan Zha, Qiang Sun
   [arxiv] [code]

7. Attention Enables Zero Approximation Error
   Zhiying Fang, Yidong Ouyang, Ding-Xuan Zhou, Guang Cheng
   [arxiv]

Conference Papers

1. Learning What Not to Impute: An Uncertainty-Aware Diffusion Framework for Meaningful Missingness
   Lixing Zhang, Yidong Ouyang, Weifu Li, Guang Cheng, Shixiang Zhu, Liyan Xie
   Annual Conference on Neural Information Processing Systems (NeurIPS), 2026
   [arxiv]

2. Corrected Samplers for Discrete Flow Models
   Zhengyan Wan, Yidong Ouyang, Liyan Xie, Fang Fang, Hongyuan Zha, Guang Cheng
   International Conference on Machine Learning (ICML), 2026
   [arxiv] [code]

3. Discrete Guidance Matching: Exact Guidance for Discrete Flow Matching
   Zhengyan Wan*, Yidong Ouyang*, Liyan Xie, Fang Fang, Hongyuan Zha, Guang Cheng
   International Conference on Learning Representations (ICLR), 2026
   [arxiv] [code]

4. Error Analysis of Discrete Flow with Generator Matching
   Zhengyan Wan, Yidong Ouyang, Qiang Yao, Liyan Xie, Fang Fang, Hongyuan Zha, Guang Cheng
   International Conference on Machine Learning (ICML), 2026
   [arxiv]

5. Transfer Learning for Diffusion Models
   Yidong Ouyang, Liyan Xie, Hongyuan Zha, Guang Cheng
   Annual Conference on Neural Information Processing Systems (NeurIPS), 2024
   [arxiv] [code]

6. MissDiff: Training Diffusion Models on Tabular Data with Missing Values
   Yidong Ouyang, Liyan Xie, Chongxuan Li, Guang Cheng
   ICML Workshop on Structured Probabilistic Inference & Generative Modeling, 2023
   [arxiv] [code]

7. Improving Adversarial Robustness Through the Contrastive-Guided Diffusion Process
   Yidong Ouyang, Liyan Xie, Guang Cheng
   International Conference on Machine Learning (ICML), 2023
   [arxiv] [code]

Journal Papers

1. Alignment of Diffusion Model and Flow Matching for Text-to-Image Generation
   Yidong Ouyang, Liyan Xie, Hongyuan Zha, Guang Cheng
   Transactions on Machine Learning Research (TMLR), 2026
   [arxiv]

2. Generalizing to Unseen Domains: A Survey on Domain Generalization
   Jindong Wang, Cuiling Lan, Chang Liu, Yidong Ouyang, Tao Qin, Wang Lu, Yiqiang Chen, Wenjun Zeng, Philip S. Yu
   IEEE Transactions on Knowledge and Data Engineering (TKDE) / IJCAI 2021 survey track
   [arxiv]

3. Learning Efficient Convolutional Networks through Irregular Convolutional Kernels
   Weiyu Guo, Jiabin Ma, Yidong Ouyang, Liang Wang, Yongzhen Huang
   Neurocomputing, 2022
   [paper]