Crafting Efficient Neural Graph of Large Entropy. - Minjing Dong; Hanting Chen; Yunhe Wang 001; Chang Xu 002 (IJCAI, 2019)

On Retrospecting Human Dynamics with Attention. - Minjing Dong; Chang Xu 002 (IJCAI, 2019)

Spatial-Temporal Attention-Based Human Dynamics Retrospection. - Minjing Dong; Chang Xu 002 (IEEE Access, 2019)

Neural Architecture Search in A Proxy Validation Loss Landscape. - Yanxi Li 001; Minjing Dong; Yunhe Wang 001; Chang Xu 002 (ICML, 2020)

An Empirical Study of Adder Neural Networks for Object Detection. - Xinghao Chen 001; Chang Xu 002; Minjing Dong; Chunjing Xu; Yunhe Wang 001 (NeurIPS, 2021)

Towards Stable and Robust AdderNets. - Minjing Dong; Yunhe Wang 001; Xinghao Chen 001; Chang Xu 002 (NeurIPS, 2021)

Handling Long-tailed Feature Distribution in AdderNets. - Minjing Dong; Yunhe Wang 001; Xinghao Chen 001; Chang Xu 002 (NeurIPS, 2021)

Spatial-Channel Token Distillation for Vision MLPs. - Yanxi Li 001; Xinghao Chen 001; Minjing Dong; Yehui Tang; Yunhe Wang 001; Chang Xu 002 (ICML, 2022)

Random Normalization Aggregation for Adversarial Defense. - Minjing Dong; Xinghao Chen 001; Yunhe Wang 001; Chang Xu 002 (NeurIPS, 2022)

Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations. - Haoyu Xie; Changqi Wang; Mingkai Zheng; Minjing Dong; Shan You; Chang Xu 002 (CoRR, 2022)

Neural architecture tuning with policy adaptation. - Yanxi Li 001; Minjing Dong; Yixing Xu; Yunhe Wang 001; Chang Xu 002 (Neurocomputing, 2022)

Neural Architecture Search for Wide Spectrum Adversarial Robustness. - Zhi Cheng; Yanxi Li 001; Minjing Dong; Xiu Su; Shan You; Chang Xu 002 (AAAI, 2023)

Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations. - Haoyu Xie; Changqi Wang; Mingkai Zheng; Minjing Dong; Shan You; Chong Fu; Chang Xu 002 (AAAI, 2023)

Adversarial Robustness via Random Projection Filters. - Minjing Dong; Chang Xu 002 (CVPR, 2023)

Dual Focal Loss for Calibration. - Linwei Tao; Minjing Dong; Chang Xu 002 (ICML, 2023)

Calibrating a Deep Neural Network with Its Predecessors. - Linwei Tao; Minjing Dong; Daochang Liu; Changming Sun; Chang Xu 002 (IJCAI, 2023)

Adversarial Robustness through Random Weight Sampling. - Yanxiang Ma; Minjing Dong; Chang Xu 002 (NeurIPS, 2023)

AMD: Autoregressive Motion Diffusion. - Bo Han; Hao Peng; Minjing Dong; Chang Xu 002; Yi Ren; Yixuan Shen; Yuheng Li (CoRR, 2023)

Parameter-Saving Adversarial Training: Reinforcing Multi-Perturbation Robustness via Hypernetworks. - Huihui Gong; Minjing Dong; Siqi Ma; Seyit Camtepe; Surya Nepal; Chang Xu 002 (CoRR, 2023)

Imitation Learning from Purified Demonstration. - Yunke Wang; Minjing Dong; Bo Du 001; Chang Xu 002 (CoRR, 2023)

Improving Lightweight AdderNet via Distillation From ℓ2 to ℓ1-norm. - Minjing Dong; Xinghao Chen 001; Yunhe Wang 001; Chang Xu 002 (IEEE Trans. Image Process., 2023)

Adversarial Recurrent Time Series Imputation. - Shuo Yang; Minjing Dong; Yunhe Wang 001; Chang Xu 002 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Neural Architecture Search via Proxy Validation. - Yanxi Li 001; Minjing Dong; Yunhe Wang 001; Chang Xu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Skeleton-Based Human Motion Prediction With Privileged Supervision. - Minjing Dong; Chang Xu 002 (IEEE Trans. Neural Networks Learn. Syst., 2023)

AMD: Autoregressive Motion Diffusion. - Bo Han; Hao Peng; Minjing Dong; Yi Ren; Yixuan Shen; Chang Xu 002 (AAAI, 2024)

Random Entangled Tokens for Adversarially Robust Vision Transformer. - Huihui Gong; Minjing Dong; Siqi Ma; Seyit Camtepe; Surya Nepal; Chang Xu 002 (CVPR, 2024)

Neural Architecture Retrieval. - Xiaohuan Pei; Yanxi Li 001; Minjing Dong; Chang Xu 002 (ICLR, 2024)

A Benchmark Study on Calibration. - Linwei Tao; Younan Zhu; Haolan Guo; Minjing Dong; Chang Xu 002 (ICLR, 2024)

Imitation Learning from Purified Demonstrations. - Yunke Wang; Minjing Dong; Yukun Zhao; Bo Du 001; Chang Xu 002 (ICML, 2024)

Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model. - Yuheng Shi; Minjing Dong; Chang Xu 002 (NeurIPS, 2024)

VSSD: Vision Mamba with Non-Casual State Space Duality. - Yuheng Shi; Minjing Dong; Mingjia Li 008; Chang Xu (CoRR, 2024)

Consistency Calibration: Improving Uncertainty Calibration via Consistency among Perturbed Neighbors. - Linwei Tao; Haolan Guo; Minjing Dong; Chang Xu 002 (CoRR, 2024)

Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Model. - Jinxu Lin; Linwei Tao; Minjing Dong; Chang Xu 002 (CoRR, 2024)

Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation. - Yuheng Shi; Minjing Dong; Chang Xu (CoRR, 2024)

Stealthy Physical Masked Face Recognition Attack via Adversarial Style Optimization. - Huihui Gong; Minjing Dong; Siqi Ma; Seyit Camtepe; Surya Nepal; Chang Xu 002 (IEEE Trans. Multim., 2024)

Efficient Image-to-Image Diffusion Classifier for Adversarial Robustness. - Hefei Mei; Minjing Dong; Chang Xu (AAAI, 2025)

Feature Clipping for Uncertainty Calibration. - Linwei Tao; Minjing Dong; Chang Xu (AAAI, 2025)

Uncertainty Weighted Gradients for Model Calibration. - Jinxu Lin; Linwei Tao; Minjing Dong; Chang Xu (CVPR, 2025)

Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models. - Jinxu Lin; Linwei Tao; Minjing Dong; Chang Xu (ICLR, 2025)

Workshop on Sustainable AI for the Future Web. - Chang Xu 002; Yunke Wang; Jianyuan Guo; Daochang Liu; Minjing Dong; Yasmeen George; Johan Barthelemy; Yan Liu 002; Ling Chen 006 (WWW (Companion Volume), 2025)

Improving Fast Adversarial Training via Self-Knowledge Guidance. - Chengze Jiang; Junkai Wang; Minjing Dong; Jie Gui; Xinli Shi; Yuan Cao 005; Yuan Yan Tang; James Tin-Yau Kwok (IEEE Trans. Inf. Forensics Secur., 2025)

Divide and Conquer: Frequency-Aware Contrastive Adversarial Training for Robust Point Cloud Classification. - Yu-Xin Zhang 004; Jie Gui; Minjing Dong; Xiaofeng Cong; Yuan Cao 005; Xin Gong; Yuan Yan Tang; James Tin-Yau Kwok (IEEE Trans. Inf. Forensics Secur., 2025)

Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration. - Younan Zhu; Linwei Tao; Minjing Dong; Chang Xu 002 (CoRR, 2025)

Survey of Adversarial Robustness in Multimodal Large Language Models. - Chengze Jiang; Zhuangzhuang Wang; Minjing Dong; Jie Gui (CoRR, 2025)

Uncertainty Weighted Gradients for Model Calibration. - Jinxu Lin; Linwei Tao; Minjing Dong; Chang Xu 002 (CoRR, 2025)

Beyond One-Hot Labels: Semantic Mixing for Model Calibration. - Haoyang Luo; Linwei Tao; Minjing Dong; Chang Xu (CoRR, 2025)

A Survey on Small Sample Imbalance Problem: Metrics, Feature Analysis, and Solutions. - Shuxian Zhao; Jie Gui; Minjing Dong; Baosheng Yu; Zhipeng Gui; Lu Dong; Yuan Yan Tang; James Tin-Yau Kwok (CoRR, 2025)

VEAttack: Downstream-agnostic Vision Encoder Attack against Large Vision Language Models. - Hefei Mei; Zirui Wang; Shen You; Minjing Dong; Chang Xu (CoRR, 2025)

Revisiting Uncertainty Estimation and Calibration of Large Language Models. - Linwei Tao; Yi-Fan Yeh; Minjing Dong; Tao Huang; Philip Torr 001; Chang Xu (CoRR, 2025)

Adversarially Robust Neural Architectures. - Minjing Dong; Yanxi Li 001; Yunhe Wang 001; Chang Xu 002 (IEEE Trans. Pattern Anal. Mach. Intell., 2025)

Sample Margin-Aware Recalibration of Temperature Scaling. - Haolan Guo; Linwei Tao; Haoyang Luo; Minjing Dong; Chang Xu 002 (CoRR, 2025)

Calibrating Graph Neural Networks with Wavelet-Aware Temperature Scaling. - Xiaoyang Li; Linwei Tao; Haohui Lu; Minjing Dong; Junbin Gao; Chang Xu (CoRR, 2025)