Hao Fang

According to our database, Hao Fang authored at least 24 papers between 2023 and 2025.

Collaborative distances:

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

2025

Revisiting the Privacy Risks of Split Inference: A GAN-Based Data Reconstruction Attack via Progressive Feature Optimization.

Yixiang Qiu, Yanhan Liu, Hongyao Yu, Hao Fang, Bin Chen, Shu-Tao Xia, Ke Xu

CoRR, August, 2025

ICAS: Detecting Training Data from Autoregressive Image Generative Models.

Hongyao Yu, Yixiang Qiu, Yiheng Yang, Hao Fang, Tianqu Zhuang, Jiaxin Hong, Bin Chen, Hao Wu, Shu-Tao Xia

CoRR, July, 2025

Grounding Language with Vision: A Conditional Mutual Information Calibrated Decoding Strategy for Reducing Hallucinations in LVLMs.

Hao Fang, Changle Zhou, Jiawei Kong, Kuofeng Gao, Bin Chen, Tao Liang, Guojun Ma, Shu-Tao Xia

CoRR, May, 2025

Wolf Hidden in Sheep's Conversations: Toward Harmless Data-Based Backdoor Attacks for Jailbreaking Large Language Models.

Jiawei Kong, Hao Fang, Xiaochen Yang, Kuofeng Gao, Bin Chen, Shu-Tao Xia, Yaowei Wang, Min Zhang

CoRR, May, 2025

Your Language Model Can Secretly Write Like Humans: Contrastive Paraphrase Attacks on LLM-Generated Text Detectors.

Hao Fang, Jiawei Kong, Tianqu Zhuang, Yixiang Qiu, Kuofeng Gao, Bin Chen, Shu-Tao Xia, Yaowei Wang, Min Zhang

CoRR, May, 2025

GaussTrap: Stealthy Poisoning Attacks on 3D Gaussian Splatting for Targeted Scene Confusion.

Jiaxin Hong, Sixu Chen, Shuoyang Sun, Hongyao Yu, Hao Fang, Yuqi Tan, Bin Chen, Shuhan Qi, Jiawei Li

CoRR, April, 2025

Neural Antidote: Class-Wise Prompt Tuning for Purifying Backdoors in Pre-trained Vision-Language Models.

Jiawei Kong, Hao Fang, Sihang Guo, Chenxi Qing, Bin Chen, Bin Wang, Shu-Tao Xia

CoRR, February, 2025

Retrievals Can Be Detrimental: A Contrastive Backdoor Attack Paradigm on Retrieval-Augmented Diffusion Models.

Hao Fang, Xiaohang Sui, Hongyao Yu, Jiawei Kong, Sijin Yu, Bin Chen, Hao Wu, Shu-Tao Xia

CoRR, January, 2025

Stealthy Shield Defense: A Conditional Mutual Information-Based Approach against Black-Box Model Inversion Attacks.

Tianqu Zhuang, Hongyao Yu, Yixiang Qiu, Hao Fang, Bin Chen, Shu-Tao Xia

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Going Beyond Feature Similarity: Effective Dataset distillation based on Class-aware Conditional Mutual Information.

Xinhao Zhong, Bin Chen, Hao Fang, Xulin Gu, Shu-Tao Xia, En-Hui Yang

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

RobNAS: Robust Neural Architecture Search for Point Cloud Adversarial Defense.

Shuoyang Sun, Kaiwen Zhang, Hao Fang, Bin Chen, Jiawei Li, Enze Huo, Shu-Tao Xia

Proceedings of the 2025 IEEE International Conference on Acoustics, 2025

Hierarchical Features Matter: A Deep Exploration of Progressive Parameterization Method for Dataset Distillation.

Xinhao Zhong, Hao Fang, Bin Chen, Xulin Gu, Meikang Qiu, Shuhan Qi, Shu-Tao Xia

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

2024

CALoR: Towards Comprehensive Model Inversion Defense.

Hongyao Yu, Yixiang Qiu, Hao Fang, Bin Chen, Sijin Yu, Bin Wang, Shu-Tao Xia, Ke Xu

CoRR, 2024

MIBench: A Comprehensive Benchmark for Model Inversion Attack and Defense.

Yixiang Qiu, Hongyao Yu, Hao Fang, Wenbo Yu, Bin Chen, Xuan Wang, Shu-Tao Xia, Ke Xu

CoRR, 2024

CLIP-Guided Networks for Transferable Targeted Attacks.

Hao Fang, Jiawei Kong, Bin Chen, Tao Dai, Hao Wu, Shu-Tao Xia

CoRR, 2024

Hierarchical Features Matter: A Deep Exploration of GAN Priors for Improved Dataset Distillation.

Xinhao Zhong, Hao Fang, Bin Chen, Xulin Gu, Tao Dai, Meikang Qiu, Shu-Tao Xia

CoRR, 2024

One Perturbation is Enough: On Generating Universal Adversarial Perturbations against Vision-Language Pre-training Models.

Hao Fang, Jiawei Kong, Wenbo Yu, Bin Chen, Jiawei Li, Shutao Xia, Ke Xu

CoRR, 2024

GI-NAS: Boosting Gradient Inversion Attacks through Adaptive Neural Architecture Search.

Wenbo Yu, Hao Fang, Bin Chen, Xiaohang Sui, Chuan Chen, Hao Wu, Shu-Tao Xia, Ke Xu

CoRR, 2024

Privacy Leakage on DNNs: A Survey of Model Inversion Attacks and Defenses.

Hao Fang, Yixiang Qiu, Hongyao Yu, Wenbo Yu, Jiawei Kong, Baoli Chong, Bin Chen, Xuan Wang, Shu-Tao Xia

CoRR, 2024

FedSMW: Server-Side Model Watermark Framework for Model Ownership Verification in Federated Learning.

Yang Cao, Hao Fang, Bin Chen, Xuan Wang, Shutao Xia

Proceedings of the 16th International Conference on Wireless Communications and Signal Processing, 2024

WaterDiff: Perceptual Image Watermarks Via Diffusion Model.

Yuqi Tan, Yuang Peng, Hao Fang, Bin Chen, Shu-Tao Xia

Proceedings of the IEEE International Conference on Acoustics, 2024

A Closer Look at GAN Priors: Exploiting Intermediate Features for Enhanced Model Inversion Attacks.

Yixiang Qiu, Hao Fang, Hongyao Yu, Bin Chen, Mei Kang Qiu, Shu-Tao Xia

Proceedings of the Computer Vision - ECCV 2024, 2024

CLIP-Guided Generative Networks for Transferable Targeted Adversarial Attacks.

Hao Fang, Jiawei Kong, Bin Chen, Tao Dai, Hao Wu, Shu-Tao Xia

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

GIFD: A Generative Gradient Inversion Method with Feature Domain Optimization.

Hao Fang, Bin Chen, Xuan Wang, Zhi Wang, Shu-Tao Xia

Proceedings of the IEEE/CVF International Conference on Computer Vision, 2023