Minjing Dong

According to our database, Minjing Dong authored at least 52 papers between 2019 and 2025.

Collaborative distances:

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

2025

Calibrating Graph Neural Networks with Wavelet-Aware Temperature Scaling.

Xiaoyang Li, Linwei Tao, Haohui Lu, Minjing Dong, Junbin Gao, Chang Xu

CoRR, June, 2025

Sample Margin-Aware Recalibration of Temperature Scaling.

Haolan Guo, Linwei Tao, Haoyang Luo, Minjing Dong, Chang Xu

CoRR, June, 2025

Adversarially Robust Neural Architectures.

Minjing Dong, Yanxi Li, Yunhe Wang, Chang Xu

IEEE Trans. Pattern Anal. Mach. Intell., May, 2025

Revisiting Uncertainty Estimation and Calibration of Large Language Models.

Linwei Tao, Yi-Fan Yeh, Minjing Dong, Tao Huang, Philip Torr, Chang Xu

CoRR, May, 2025

VEAttack: Downstream-agnostic Vision Encoder Attack against Large Vision Language Models.

Hefei Mei, Zirui Wang, Shen You, Minjing Dong, Chang Xu

CoRR, May, 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, April, 2025

Beyond One-Hot Labels: Semantic Mixing for Model Calibration.

Haoyang Luo, Linwei Tao, Minjing Dong, Chang Xu

CoRR, April, 2025

Uncertainty Weighted Gradients for Model Calibration.

Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu

CoRR, March, 2025

Survey of Adversarial Robustness in Multimodal Large Language Models.

Chengze Jiang, Zhuangzhuang Wang, Minjing Dong, Jie Gui

CoRR, March, 2025

Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration.

Younan Zhu, Linwei Tao, Minjing Dong, Chang Xu

CoRR, February, 2025

Divide and Conquer: Frequency-Aware Contrastive Adversarial Training for Robust Point Cloud Classification.

Yu-Xin Zhang, Jie Gui, Minjing Dong, Xiaofeng Cong, Yuan Cao, Xin Gong, Yuan Yan Tang, James Tin-Yau Kwok

IEEE Trans. Inf. Forensics Secur., 2025

Improving Fast Adversarial Training via Self-Knowledge Guidance.

Chengze Jiang, Junkai Wang, Minjing Dong, Jie Gui, Xinli Shi, Yuan Cao, Yuan Yan Tang, James Tin-Yau Kwok

IEEE Trans. Inf. Forensics Secur., 2025

Workshop on Sustainable AI for the Future Web.

Chang Xu, Yunke Wang, Jianyuan Guo, Daochang Liu, Minjing Dong, Yasmeen George, Johan Barthelemy, Yan Liu, Ling Chen

Proceedings of the Companion Proceedings of the ACM on Web Conference 2025, 2025

Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Models.

Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Uncertainty Weighted Gradients for Model Calibration.

Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Feature Clipping for Uncertainty Calibration.

Linwei Tao, Minjing Dong, Chang Xu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

Efficient Image-to-Image Diffusion Classifier for Adversarial Robustness.

Hefei Mei, Minjing Dong, Chang Xu

Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024

Stealthy Physical Masked Face Recognition Attack via Adversarial Style Optimization.

Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu

IEEE Trans. Multim., 2024

Harnessing Vision Foundation Models for High-Performance, Training-Free Open Vocabulary Segmentation.

Yuheng Shi, Minjing Dong, Chang Xu

CoRR, 2024

Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Model.

Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu

CoRR, 2024

Consistency Calibration: Improving Uncertainty Calibration via Consistency among Perturbed Neighbors.

Linwei Tao, Haolan Guo, Minjing Dong, Chang Xu

CoRR, 2024

VSSD: Vision Mamba with Non-Casual State Space Duality.

Yuheng Shi, Minjing Dong, Mingjia Li, Chang Xu

CoRR, 2024

Multi-Scale VMamba: Hierarchy in Hierarchy Visual State Space Model.

Yuheng Shi, Minjing Dong, Chang Xu

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

Imitation Learning from Purified Demonstrations.

Yunke Wang, Minjing Dong, Yukun Zhao, Bo Du, Chang Xu

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

A Benchmark Study on Calibration.

Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Neural Architecture Retrieval.

Xiaohuan Pei, Yanxi Li, Minjing Dong, Chang Xu

Proceedings of the Twelfth International Conference on Learning Representations, 2024

Random Entangled Tokens for Adversarially Robust Vision Transformer.

Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2024

AMD: Autoregressive Motion Diffusion.

Bo Han, Hao Peng, Minjing Dong, Yi Ren, Yixuan Shen, Chang Xu

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

Skeleton-Based Human Motion Prediction With Privileged Supervision.

Minjing Dong, Chang Xu

IEEE Trans. Neural Networks Learn. Syst., December, 2023

Neural Architecture Search via Proxy Validation.

Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu

IEEE Trans. Pattern Anal. Mach. Intell., June, 2023

Adversarial Recurrent Time Series Imputation.

Shuo Yang, Minjing Dong, Yunhe Wang, Chang Xu

IEEE Trans. Neural Networks Learn. Syst., April, 2023

Improving Lightweight AdderNet via Distillation From ℓ₂ to ℓ₁-norm.

Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu

IEEE Trans. Image Process., 2023

Imitation Learning from Purified Demonstration.

Yunke Wang, Minjing Dong, Bo Du, Chang Xu

CoRR, 2023

Parameter-Saving Adversarial Training: Reinforcing Multi-Perturbation Robustness via Hypernetworks.

Huihui Gong, Minjing Dong, Siqi Ma, Seyit Camtepe, Surya Nepal, Chang Xu

CoRR, 2023

AMD: Autoregressive Motion Diffusion.

Bo Han, Hao Peng, Minjing Dong, Chang Xu, Yi Ren, Yixuan Shen, Yuheng Li

CoRR, 2023

Adversarial Robustness through Random Weight Sampling.

Yanxiang Ma, Minjing Dong, Chang Xu

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

Calibrating a Deep Neural Network with Its Predecessors.

Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu

Proceedings of the Thirty-Second International Joint Conference on Artificial Intelligence, 2023

Dual Focal Loss for Calibration.

Linwei Tao, Minjing Dong, Chang Xu

Proceedings of the International Conference on Machine Learning, 2023

Adversarial Robustness via Random Projection Filters.

Minjing Dong, Chang Xu

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations.

Haoyu Xie, Changqi Wang, Mingkai Zheng, Minjing Dong, Shan You, Chong Fu, Chang Xu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Neural Architecture Search for Wide Spectrum Adversarial Robustness.

Zhi Cheng, Yanxi Li, Minjing Dong, Xiu Su, Shan You, Chang Xu

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

Neural architecture tuning with policy adaptation.

Yanxi Li, Minjing Dong, Yixing Xu, Yunhe Wang, Chang Xu

Neurocomputing, 2022

Boosting Semi-Supervised Semantic Segmentation with Probabilistic Representations.

Haoyu Xie, Changqi Wang, Mingkai Zheng, Minjing Dong, Shan You, Chang Xu

CoRR, 2022

Random Normalization Aggregation for Adversarial Defense.

Minjing Dong, Xinghao Chen, Yunhe Wang, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Spatial-Channel Token Distillation for Vision MLPs.

Yanxi Li, Xinghao Chen, Minjing Dong, Yehui Tang, Yunhe Wang, Chang Xu

Proceedings of the International Conference on Machine Learning, 2022

2021

Handling Long-tailed Feature Distribution in AdderNets.

Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

Towards Stable and Robust AdderNets.

Minjing Dong, Yunhe Wang, Xinghao Chen, Chang Xu

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

An Empirical Study of Adder Neural Networks for Object Detection.

Xinghao Chen, Chang Xu, Minjing Dong, Chunjing Xu, Yunhe Wang

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Neural Architecture Search in A Proxy Validation Loss Landscape.

Yanxi Li, Minjing Dong, Yunhe Wang, Chang Xu

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

2019

Spatial-Temporal Attention-Based Human Dynamics Retrospection.

Minjing Dong, Chang Xu

IEEE Access, 2019

On Retrospecting Human Dynamics with Attention.

Minjing Dong, Chang Xu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Crafting Efficient Neural Graph of Large Entropy.

Minjing Dong, Hanting Chen, Yunhe Wang, Chang Xu

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019