Han Xu

According to our database, Han Xu authored at least 40 papers between 2020 and 2024.

Collaborative distances:

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

2024

Mitigating the Privacy Issues in Retrieval-Augmented Generation (RAG) via Pure Synthetic Data.

Shenglai Zeng, Jiankun Zhang, Pengfei He, Jie Ren, Tianqi Zheng, Hanqing Lu, Han Xu, Hui Liu, Yue Xing, Jiliang Tang

CoRR, 2024

Towards Understanding Jailbreak Attacks in LLMs: A Representation Space Analysis.

Yuping Lin, Pengfei He, Han Xu, Yue Xing, Makoto Yamada, Hui Liu, Jiliang Tang

CoRR, 2024

Unveiling and Mitigating Memorization in Text-to-image Diffusion Models through Cross Attention.

Jie Ren, Yaxin Li, Shenglai Zeng, Han Xu, Lingjuan Lyu, Yue Xing, Jiliang Tang

CoRR, 2024

Copyright Protection in Generative AI: A Technical Perspective.

Jie Ren, Han Xu, Pengfei He, Yingqian Cui, Shenglai Zeng, Jiankun Zhang, Hongzhi Wen, Jiayuan Ding, Hui Liu, Yi Chang, Jiliang Tang

CoRR, 2024

Data Poisoning for In-context Learning.

Pengfei He, Han Xu, Yue Xing, Hui Liu, Makoto Yamada, Jiliang Tang

CoRR, 2024

Neural Style Protection: Counteracting Unauthorized Neural Style Transfer.

Yaxin Li, Jie Ren, Han Xu, Hui Liu

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

Sharpness-Aware Data Poisoning Attack.

Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Shenglai Zeng, Hui Liu, Charu C. Aggarwal, Jiliang Tang

Proceedings of the Twelfth International Conference on Learning Representations, 2024

The Good and The Bad: Exploring Privacy Issues in Retrieval-Augmented Generation (RAG).

Shenglai Zeng, Jiankun Zhang, Pengfei He, Yiding Liu, Yue Xing, Han Xu, Jie Ren, Yi Chang, Shuaiqiang Wang, Dawei Yin, Jiliang Tang

Proceedings of the Findings of the Association for Computational Linguistics, 2024

Exploring Memorization in Fine-tuned Language Models.

Shenglai Zeng, Yaxin Li, Jie Ren, Yiding Liu, Han Xu, Pengfei He, Yue Xing, Shuaiqiang Wang, Jiliang Tang, Dawei Yin

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

A Robust Semantics-based Watermark for Large Language Model against Paraphrasing.

Jie Ren, Han Xu, Yiding Liu, Yingqian Cui, Shuaiqiang Wang, Dawei Yin, Jiliang Tang

CoRR, 2023

Confidence-driven Sampling for Backdoor Attacks.

Pengfei He, Han Xu, Yue Xing, Jie Ren, Yingqian Cui, Shenglai Zeng, Jiliang Tang, Makoto Yamada, Mohammad Sabokrou

CoRR, 2023

FT-Shield: A Watermark Against Unauthorized Fine-tuning in Text-to-Image Diffusion Models.

Yingqian Cui, Jie Ren, Yuping Lin, Han Xu, Pengfei He, Yue Xing, Wenqi Fan, Hui Liu, Jiliang Tang

CoRR, 2023

On the Generalization of Training-based ChatGPT Detection Methods.

Han Xu, Jie Ren, Pengfei He, Shenglai Zeng, Yingqian Cui, Amy Liu, Hui Liu, Jiliang Tang

CoRR, 2023

DiffusionShield: A Watermark for Copyright Protection against Generative Diffusion Models.

Yingqian Cui, Jie Ren, Han Xu, Pengfei He, Hui Liu, Lichao Sun, Jiliang Tang

CoRR, 2023

Sharpness-Aware Data Poisoning Attack.

Pengfei He, Han Xu, Jie Ren, Yingqian Cui, Hui Liu, Charu C. Aggarwal, Jiliang Tang

CoRR, 2023

How does the Memorization of Neural Networks Impact Adversarial Robust Models?

Han Xu, Xiaorui Liu, Wentao Wang, Zitao Liu, Anil K. Jain, Jiliang Tang

Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Probabilistic Categorical Adversarial Attack and Adversarial Training.

Han Xu, Pengfei He, Jie Ren, Yuxuan Wan, Zitao Liu, Hui Liu, Jiliang Tang

Proceedings of the International Conference on Machine Learning, 2023

Transferable Unlearnable Examples.

Jie Ren, Han Xu, Yuxuan Wan, Xingjun Ma, Lichao Sun, Jiliang Tang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

Jointly Attacking Graph Neural Network and its Explanations.

Wenqi Fan, Han Xu, Wei Jin, Xiaorui Liu, Xianfeng Tang, Suhang Wang, Qing Li, Jiliang Tang, Jianping Wang, Charu C. Aggarwal

Proceedings of the 39th IEEE International Conference on Data Engineering, 2023

2022

Towards Fair Classification against Poisoning Attacks.

Han Xu, Xiaorui Liu, Yuxuan Wan, Jiliang Tang

CoRR, 2022

Probabilistic Categorical Adversarial Attack & Adversarial Training.

Pengfei He, Han Xu, Jie Ren, Yuxuan Wan, Zitao Liu, Jiliang Tang

CoRR, 2022

A Comprehensive Survey on Trustworthy Recommender Systems.

Wenqi Fan, Xiangyu Zhao, Xiao Chen, Jingran Su, Jingtong Gao, Lin Wang, Qidong Liu, Yiqi Wang, Han Xu, Lei Chen, Qing Li

CoRR, 2022

Defense Against Gradient Leakage Attacks via Learning to Obscure Data.

Yuxuan Wan, Han Xu, Xiaorui Liu, Jie Ren, Wenqi Fan, Jiliang Tang

CoRR, 2022

Enhancing Adversarial Training with Feature Separability.

Yaxin Li, Xiaorui Liu, Han Xu, Wentao Wang, Jiliang Tang

CoRR, 2022

Doctoral Consortium of WSDM'22: Exploring the Bias of Adversarial Defenses.

Han Xu

Proceedings of the WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21, 2022

Towards Adversarial Learning: From Evasion Attacks to Poisoning Attacks.

Wentao Wang, Han Xu, Yuxuan Wan, Jie Ren, Jiliang Tang

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

Imbalanced Adversarial Training with Reweighting.

Wentao Wang, Han Xu, Xiaorui Liu, Yaxin Li, Bhavani Thuraisingham, Jiliang Tang

Proceedings of the IEEE International Conference on Data Mining, 2022

2021

Towards the Memorization Effect of Neural Networks in Adversarial Training.

Han Xu, Xiaorui Liu, Wentao Wang, Wenbiao Ding, Zhongqin Wu, Zitao Liu, Anil K. Jain, Jiliang Tang

CoRR, 2021

Yet Meta Learning Can Adapt Fast, it Can Also Break Easily.

Han Xu, Yaxin Li, Xiaorui Liu, Hui Liu, Jiliang Tang

Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Graph Neural Networks with Adaptive Residual.

Xiaorui Liu, Jiayuan Ding, Wei Jin, Han Xu, Yao Ma, Zitao Liu, Jiliang Tang

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

Adversarial Robustness in Deep Learning: From Practices to Theories.

Han Xu, Yaxin Li, Xiaorui Liu, Wentao Wang, Jiliang Tang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

To be Robust or to be Fair: Towards Fairness in Adversarial Training.

Han Xu, Xiaorui Liu, Yaxin Li, Anil K. Jain, Jiliang Tang

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

DeepRobust: a Platform for Adversarial Attacks and Defenses.

Yaxin Li, Wei Jin, Han Xu, Jiliang Tang

Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020

Adversarial Attacks and Defenses on Graphs.

Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Shuiwang Ji, Charu Aggarwal, Jiliang Tang

SIGKDD Explor., 2020

Adversarial Attacks and Defenses in Images, Graphs and Text: A Review.

Han Xu, Yao Ma, Haochen Liu, Debayan Deb, Hui Liu, Jiliang Tang, Anil K. Jain

Int. J. Autom. Comput., 2020

To be Robust or to be Fair: Towards Fairness in Adversarial Training.

Han Xu, Xiaorui Liu, Yaxin Li, Jiliang Tang

CoRR, 2020

DeepRobust: A PyTorch Library for Adversarial Attacks and Defenses.

Yaxin Li, Wei Jin, Han Xu, Jiliang Tang

CoRR, 2020

Adversarial Attacks and Defenses on Graphs: A Review and Empirical Study.

Wei Jin, Yaxin Li, Han Xu, Yiqi Wang, Jiliang Tang

CoRR, 2020

Deep Adversarial Canonical Correlation Analysis.

Wenqi Fan, Yao Ma, Han Xu, Xiaorui Liu, Jianping Wang, Qing Li, Jiliang Tang

Proceedings of the 2020 SIAM International Conference on Data Mining, 2020

Adversarial Attacks and Defenses: Frontiers, Advances and Practice.

Han Xu, Yaxin Li, Wei Jin, Jiliang Tang

Proceedings of the KDD '20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2020