| 2026 | AAAI | Diversifying Counterattacks: Orthogonal Exploration for Robust CLlP Inference. | Chengze Jiang, Minjing Dong, Xinli Shi, Jie Gui |
| 2025 | AAAI | Efficient Image-to-Image Diffusion Classifier for Adversarial Robustness. | Hefei Mei, Minjing Dong, Chang Xu |
| 2025 | AAAI | Feature Clipping for Uncertainty Calibration. | Linwei Tao, Minjing Dong, Chang Xu |
| 2025 | CVPR | Uncertainty Weighted Gradients for Model Calibration. | Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu |
| 2025 | ICCV | Backdooring Self-Supervised Contrastive Learning by Noisy Alignment. | Tuo Chen, Jie Gui, Minjing Dong, Ju Jia, Lanting Fang, Jian Liu |
| 2025 | ICCV | Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation. | Yuheng Shi, Minjing Dong, Chang Xu |
| 2025 | ICCV | VSSD: Vision Mamba With Non-Causal State Space Duality. | Yuheng Shi, Mingjia Li, Minjing Dong, Chang Xu |
| 2025 | ICLR | Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models. | Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu |
| 2025 | ICML | Beyond One-Hot Labels: Semantic Mixing for Model Calibration. | Haoyang Luo, Linwei Tao, Minjing Dong, Chang Xu |
| 2025 | ICML | Adversarial Robustness via Deformable Convolution with Stochasticity. | Yanxiang Ma, Zixuan Huang, Minjing Dong, Shan You, Chang Xu |
| 2025 | WWW | Workshop on Sustainable AI for the Future Web. | Chang Xu, Yunke Wang, Jianyuan Guo, Daochang Liu, Minjing Dong, Yasmeen M. George, Johan Barthelemy, Yan Liu, Ling Chen |
| 2024 | AAAI | AMD: Autoregressive Motion Diffusion. | Bo Han, Hao Peng, Minjing Dong, Yi Ren, Yixuan Shen, Chang Xu |
| 2024 | CVPR | Random Entangled Tokens for Adversarially Robust Vision Transformer. | Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu |
| 2024 | ICLR | Neural Architecture Retrieval. | Xiaohuan Pei, Yanxi Li, Minjing Dong, Chang Xu |
| 2024 | ICLR | A Benchmark Study on Calibration. | Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu |
| 2024 | ICML | Imitation Learning from Purified Demonstrations. | Yunke Wang, Minjing Dong, Yukun Zhao, Bo Du, Chang Xu |
| 2023 | AAAI | Neural Architecture Search for Wide Spectrum Adversarial Robustness. | Zhi Cheng, Yanxi Li, Minjing Dong, Xiu Su, Shan You, Chang Xu |
| 2023 | AAAI | Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations. | Haoyu Xie, Changqi Wang, Mingkai Zheng, Minjing Dong, Shan You, Chong Fu, Chang Xu |
| 2023 | CVPR | Adversarial Robustness via Random Projection Filters. | Minjing Dong, Chang Xu |
| 2023 | ICML | Dual Focal Loss for Calibration. | Linwei Tao, Minjing Dong, Chang Xu |
| 2023 | IJCAI | Calibrating a Deep Neural Network with Its Predecessors. | Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu |
| 2022 | ICML | Spatial-Channel Token Distillation for Vision MLPs. | Yanxi Li, Xinghao Chen, Minjing Dong, Yehui Tang, Yunhe Wang, Chang Xu |
| 2020 | ICML | Neural Architecture Search in A Proxy Validation Loss Landscape. | Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu |
| 2019 | IJCAI | Crafting Efficient Neural Graph of Large Entropy. | Minjing Dong, Hanting Chen, Yunhe Wang, Chang Xu |
| 2019 | IJCAI | On Retrospecting Human Dynamics with Attention. | Minjing Dong, Chang Xu |