| 2025 | CVPR | Towards Better Alignment: Training Diffusion Models with Reinforcement Learning Against Sparse Rewards. | Zijing Hu, Fengda Zhang, Long Chen, Kun Kuang, Jiahui Li, Kaifeng Gao, Jun Xiao, Xin Wang, Wenwu Zhu |
| 2025 | ICCV | Decoding Correlation-Induced Misalignment in the Stable Diffusion Workflow for Text-to-Image Generation. | Yunze Tong, Fengda Zhang, Didi Zhu, Jun Xiao, Kun Kuang |
| 2025 | ICML | D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples. | Zijing Hu, Fengda Zhang, Kun Kuang |
| 2025 | ICML | Latent Score-Based Reweighting for Robust Classification on Imbalanced Tabular Data. | Yunze Tong, Fengda Zhang, Zihao Tang, Kaifeng Gao, Kai Huang, Pengfei Lyu, Jun Xiao, Kun Kuang |
| 2024 | CVPR | Distributionally Generative Augmentation for Fair Facial Attribute Classification. | Fengda Zhang, Qianpei He, Kun Kuang, Jiashuo Liu, Long Chen, Chao Wu, Jun Xiao, Hanwang Zhang |
| 2024 | EMNLP | Optimizing Language Models with Fair and Stable Reward Composition in Reinforcement Learning. | Jiahui Li, Hanlin Zhang, Fengda Zhang, Tai-Wei Chang, Kun Kuang, Long Chen, Jun Zhou |
| 2023 | ICLR | Fairness-aware Contrastive Learning with Partially Annotated Sensitive Attributes. | Fengda Zhang, Kun Kuang, Long Chen, Yuxuan Liu, Chao Wu, Jun Xiao |