Jingfeng Zhang

According to our database, Jingfeng Zhang authored at least 53 papers between 2018 and 2024.

Collaborative distances:

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

2024

Learning a robust foundation model against clean-label data poisoning attacks at downstream tasks.

Ting Zhou, Hanshu Yan, Bo Han, Lei Liu, Jingfeng Zhang

Neural Networks, January, 2024

Locate, Assign, Refine: Taming Customized Image Inpainting with Text-Subject Guidance.

Yulin Pan, Chaojie Mao, Zeyinzi Jiang, Zhen Han, Jingfeng Zhang

CoRR, 2024

Make Me Happier: Evoking Emotions Through Image Diffusion Models.

Qing Lin, Jingfeng Zhang, Yew Soon Ong, Mengmi Zhang

CoRR, 2024

Privacy-Preserving Low-Rank Adaptation for Latent Diffusion Models.

Zihao Luo, Xilie Xu, Feng Liu, Yun Sing Koh, Di Wang, Jingfeng Zhang

CoRR, 2024

2023

Decision Boundary-Aware Data Augmentation for Adversarial Training.

Chen Chen, Jingfeng Zhang, Xilie Xu, Lingjuan Lyu, Chaochao Chen, Tianlei Hu, Gang Chen

IEEE Trans. Dependable Secur. Comput., 2023

SCEdit: Efficient and Controllable Image Diffusion Generation via Skip Connection Editing.

Zeyinzi Jiang, Chaojie Mao, Yulin Pan, Zhen Han, Jingfeng Zhang

CoRR, 2023

Fair Text-to-Image Diffusion via Fair Mapping.

Jia Li, Lijie Hu, Jingfeng Zhang, Tianhang Zheng, Hua Zhang, Di Wang

CoRR, 2023

An LLM can Fool Itself: A Prompt-Based Adversarial Attack.

Xilie Xu, Keyi Kong, Ning Liu, Lizhen Cui, Di Wang, Jingfeng Zhang, Mohan S. Kankanhalli

CoRR, 2023

AutoLoRa: A Parameter-Free Automated Robust Fine-Tuning Framework.

Xilie Xu, Jingfeng Zhang, Mohan S. Kankanhalli

CoRR, 2023

BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning.

Jingfeng Zhang, Bo Song, Haohan Wang, Bo Han, Tongliang Liu, Lei Liu, Masashi Sugiyama

CoRR, 2023

Assessing Vulnerabilities of Adversarial Learning Algorithm through Poisoning Attacks.

Jingfeng Zhang, Bo Song, Bo Han, Lei Liu, Gang Niu, Masashi Sugiyama

CoRR, 2023

Efficient Adversarial Contrastive Learning via Robustness-Aware Coreset Selection.

Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli

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

Enhancing Adversarial Contrastive Learning via Adversarial Invariant Regularization.

Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli

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

GAT: Guided Adversarial Training with Pareto-optimal Auxiliary Tasks.

Salah Ghamizi, Jingfeng Zhang, Maxime Cordy, Mike Papadakis, Masashi Sugiyama, Yves Le Traon

Proceedings of the International Conference on Machine Learning, 2023

2022

XCode: Towards Cross-Language Code Representation with Large-Scale Pre-Training.

Zehao Lin, Guodun Li, Jingfeng Zhang, Yue Deng, Xiangji Zeng, Yin Zhang, Yao Wan

ACM Trans. Softw. Eng. Methodol., 2022

NoiLin: Improving adversarial training and correcting stereotype of noisy labels.

Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Lizhen Cui, Gang Niu, Masashi Sugiyama

Trans. Mach. Learn. Res., 2022

Uncertainty-guided graph attention network for parapneumonic effusion diagnosis.

Jinkui Hao, Jiang Liu, Ella Pereira, Ri Liu, Jiong Zhang, Yangfan Zhang, Kun Yan, Yan Gong, Jianjun Zheng, Jingfeng Zhang, Yonghuai Liu, Yitian Zhao

Medical Image Anal., 2022

FuncFooler: A Practical Black-box Attack Against Learning-based Binary Code Similarity Detection Methods.

Lichen Jia, Bowen Tang, Chenggang Wu, Zhe Wang, Zihan Jiang, Yuanming Lai, Yan Kang, Ning Liu, Jingfeng Zhang

CoRR, 2022

Accelerating Score-based Generative Models for High-Resolution Image Synthesis.

Hengyuan Ma, Li Zhang, Xiatian Zhu, Jingfeng Zhang, Jianfeng Feng

CoRR, 2022

WaveFuzz: A Clean-Label Poisoning Attack to Protect Your Voice.

Yunjie Ge, Qian Wang, Jingfeng Zhang, Juntao Zhou, Yunzhu Zhang, Chao Shen

CoRR, 2022

On the Effectiveness of Adversarial Training against Backdoor Attacks.

Yinghua Gao, Dongxian Wu, Jingfeng Zhang, Guanhao Gan, Shu-Tao Xia, Gang Niu, Masashi Sugiyama

CoRR, 2022

Adversarial Attacks and Defense for Non-Parametric Two-Sample Tests.

Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli

CoRR, 2022

Improved Dynamic Contrast-Enhanced MRI Using Low Rank With Joint Sparsity.

Jichang Zhang, Faisal Najeeb, Xinpei Wang, Pengfei Xu, Hammad Omer, Jianjun Zheng, Jingfeng Zhang, Sue Francis, Paul Glover, Richard Bowtell, Chengbo Wang

IEEE Access, 2022

Synergy-of-Experts: Collaborate to Improve Adversarial Robustness.

Sen Cui, Jingfeng Zhang, Jian Liang, Bo Han, Masashi Sugiyama, Changshui Zhang

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

Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative Attacks.

Jianan Zhou, Jianing Zhu, Jingfeng Zhang, Tongliang Liu, Gang Niu, Bo Han, Masashi Sugiyama

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

Bilateral Dependency Optimization: Defending Against Model-inversion Attacks.

Xiong Peng, Feng Liu, Jingfeng Zhang, Long Lan, Junjie Ye, Tongliang Liu, Bo Han

Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Towards Adversarially Robust Deep Image Denoising.

Hanshu Yan, Jingfeng Zhang, Jiashi Feng, Masashi Sugiyama, Vincent Y. F. Tan

Proceedings of the Thirty-First International Joint Conference on Artificial Intelligence, 2022

Adversarial Attack and Defense for Non-Parametric Two-Sample Tests.

Xilie Xu, Jingfeng Zhang, Feng Liu, Masashi Sugiyama, Mohan S. Kankanhalli

Proceedings of the International Conference on Machine Learning, 2022

Diverse Instance Discovery: Vision-Transformer for Instance-Aware Multi-Label Image Recognition.

Yunqing Hu, Xuan Jin, Yin Zhang, Haiwen Hong, Jingfeng Zhang, Feihu Yan, Yuan He, Hui Xue

Proceedings of the IEEE International Conference on Multimedia and Expo, 2022

Reliable Adversarial Distillation with Unreliable Teachers.

Jianing Zhu, Jiangchao Yao, Bo Han, Jingfeng Zhang, Tongliang Liu, Gang Niu, Jingren Zhou, Jianliang Xu, Hongxia Yang

Proceedings of the Tenth International Conference on Learning Representations, 2022

Pulmonary Nodule Detection Based on RPN with Squeeze-and-Excitation Block.

Xiaoxi Lu, Xingyue Wang, Jiansheng Fang, Na Zeng, Yao Xiang, Jingfeng Zhang, Jianjun Zheng, Jiang Liu

Proceedings of the 2022 The 5th International Conference on Control and Computer Vision, 2022

2021

A Tapered Soft Robotic Oropharyngeal Swab for Throat Testing: A New Way to Collect Sputa Samples.

Zhexin Xie, Bohan Chen, Jiaqi Liu, Feiyang Yuan, Zhuyin Shao, Hui Yang, August G. Domel, Jingfeng Zhang, Li Wen

IEEE Robotics Autom. Mag., 2021

RAMS-Trans: Recurrent Attention Multi-scale Transformer forFine-grained Image Recognition.

Yunqing Hu, Xuan Jin, Yin Zhang, Haiwen Hong, Jingfeng Zhang, Yuan He, Hui Xue

CoRR, 2021

NoiLIn: Do Noisy Labels Always Hurt Adversarial Training?

Jingfeng Zhang, Xilie Xu, Bo Han, Tongliang Liu, Gang Niu, Lizhen Cui, Masashi Sugiyama

CoRR, 2021

Guided Interpolation for Adversarial Training.

Chen Chen, Jingfeng Zhang, Xilie Xu, Tianlei Hu, Gang Niu, Gang Chen, Masashi Sugiyama

CoRR, 2021

Understanding the Interaction of Adversarial Training with Noisy Labels.

Jianing Zhu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Hongxia Yang, Mohan S. Kankanhalli, Masashi Sugiyama

CoRR, 2021

RAMS-Trans: Recurrent Attention Multi-scale Transformer for Fine-grained Image Recognition.

Yunqing Hu, Xuan Jin, Yin Zhang, Haiwen Hong, Jingfeng Zhang, Yuan He, Hui Xue

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

DRDF: Determining the Importance of Different Multimodal Information with Dual-Router Dynamic Framework.

Haiwen Hong, Xuan Jin, Yin Zhang, Yunqing Hu, Jingfeng Zhang, Yuan He, Hui Xue

Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

CIFS: Improving Adversarial Robustness of CNNs via Channel-wise Importance-based Feature Selection.

Hanshu Yan, Jingfeng Zhang, Gang Niu, Jiashi Feng, Vincent Y. F. Tan, Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 2021

Maximum Mean Discrepancy Test is Aware of Adversarial Attacks.

Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 2021

Learning Diverse-Structured Networks for Adversarial Robustness.

Xuefeng Du, Jingfeng Zhang, Bo Han, Tongliang Liu, Yu Rong, Gang Niu, Junzhou Huang, Masashi Sugiyama

Proceedings of the 38th International Conference on Machine Learning, 2021

Geometry-aware Instance-reweighted Adversarial Training.

Jingfeng Zhang, Jianing Zhu, Gang Niu, Bo Han, Masashi Sugiyama, Mohan S. Kankanhalli

Proceedings of the 9th International Conference on Learning Representations, 2021

Fix-Filter-Fix: Intuitively Connect Any Models for Effective Bug Fixing.

Haiwen Hong, Jingfeng Zhang, Yin Zhang, Yao Wan, Yulei Sui

Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, 2021

Disentangled Code Representation Learning for Multiple Programming Languages.

Jingfeng Zhang, Haiwen Hong, Yin Zhang, Yao Wan, Ye Liu, Yulei Sui

Proceedings of the Findings of the Association for Computational Linguistics: ACL/IJCNLP 2021, 2021

2020

Maximum Mean Discrepancy is Aware of Adversarial Attacks.

Ruize Gao, Feng Liu, Jingfeng Zhang, Bo Han, Tongliang Liu, Gang Niu, Masashi Sugiyama

CoRR, 2020

Robust Federated Recommendation System.

Chen Chen, Jingfeng Zhang, Anthony K. H. Tung, Mohan S. Kankanhalli, Gang Chen

CoRR, 2020

Hierarchically Fair Federated Learning.

Jingfeng Zhang, Cheng Li, Antonio Robles-Kelly, Mohan S. Kankanhalli

CoRR, 2020

Attacks Which Do Not Kill Training Make Adversarial Learning Stronger.

Jingfeng Zhang, Xilie Xu, Bo Han, Gang Niu, Lizhen Cui, Masashi Sugiyama, Mohan S. Kankanhalli

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

2019

Facilitating HPC Operation and Administration via Cloud.

Chaoqun Sha, Jingfeng Zhang, Lei An, Yongsheng Zhang, Zhipeng Wang, Tomi Ilijas, Nejc Bat, Miha Verlic, Qing Ji

Supercomput. Front. Innov., 2019

Experimental and Numerical Investigation on the Ultimate Vertical Bearing Capacity of U-Shaped Girder with Damaged Web.

Jingfeng Zhang, Yuan Jing, Pandao Li, Wanshui Han, Nan Zhang, Yun-Lai Zhou

Sensors, 2019

Where is the Bottleneck of Adversarial Learning with Unlabeled Data?

Jingfeng Zhang, Bo Han, Gang Niu, Tongliang Liu, Masashi Sugiyama

CoRR, 2019

Towards Robust ResNet: A Small Step but a Giant Leap.

Jingfeng Zhang, Bo Han, Laura Wynter, Bryan Kian Hsiang Low, Mohan S. Kankanhalli

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

2018

Smooth Inter-layer Propagation of Stabilized Neural Networks for Classification.

Jingfeng Zhang, Laura Wynter

CoRR, 2018