Saved in:
| Main Authors: | Meng, Jiayang, Huang, Tao, Hou, Chen, Zheng, Guolong, Chen, Hong |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2602.22611 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DP-aware AdaLN-Zero: Taming Conditioning-Induced Heavy-Tailed Gradients in Differentially Private Diffusion
by: Huang, Tao, et al.
Published: (2026)
by: Huang, Tao, et al.
Published: (2026)
Intermediate Outputs Are More Sensitive Than You Think
by: Huang, Tao, et al.
Published: (2024)
by: Huang, Tao, et al.
Published: (2024)
Enhancing DP-SGD through Non-monotonous Adaptive Scaling Gradient Weight
by: Huang, Tao, et al.
Published: (2024)
by: Huang, Tao, et al.
Published: (2024)
Enhanced Privacy Leakage from Noise-Perturbed Gradients via Gradient-Guided Conditional Diffusion Models
by: Meng, Jiayang, et al.
Published: (2025)
by: Meng, Jiayang, et al.
Published: (2025)
Real-Time Privacy Risk Measurement with Privacy Tokens for Gradient Leakage
by: Meng, Jiayang, et al.
Published: (2025)
by: Meng, Jiayang, et al.
Published: (2025)
Gradient-Guided Conditional Diffusion Models for Private Image Reconstruction: Analyzing Adversarial Impacts of Differential Privacy and Denoising
by: Huang, Tao, et al.
Published: (2024)
by: Huang, Tao, et al.
Published: (2024)
Bayesian Inference of Training Dataset Membership
by: Huang, Yongchao
Published: (2025)
by: Huang, Yongchao
Published: (2025)
Range Membership Inference Attacks
by: Tao, Jiashu, et al.
Published: (2024)
by: Tao, Jiashu, et al.
Published: (2024)
Secure Aggregation is Not Private Against Membership Inference Attacks
by: Ngo, Khac-Hoang, et al.
Published: (2024)
by: Ngo, Khac-Hoang, et al.
Published: (2024)
DCMI: A Differential Calibration Membership Inference Attack Against Retrieval-Augmented Generation
by: Gao, Xinyu, et al.
Published: (2025)
by: Gao, Xinyu, et al.
Published: (2025)
AdaMixup: A Dynamic Defense Framework for Membership Inference Attack Mitigation
by: Chen, Ying, et al.
Published: (2025)
by: Chen, Ying, et al.
Published: (2025)
Mitigating Membership Inference Vulnerability in Personalized Federated Learning
by: Jung, Kangsoo, et al.
Published: (2025)
by: Jung, Kangsoo, et al.
Published: (2025)
Imitative Membership Inference Attack
by: Du, Yuntao, et al.
Published: (2025)
by: Du, Yuntao, et al.
Published: (2025)
Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss
by: Liu, Zhenlong, et al.
Published: (2024)
by: Liu, Zhenlong, et al.
Published: (2024)
MIST: Defending Against Membership Inference Attacks Through Membership-Invariant Subspace Training
by: Li, Jiacheng, et al.
Published: (2023)
by: Li, Jiacheng, et al.
Published: (2023)
Auditing Training Data in Generative Music Models via Black-Box Membership Inference
by: Liu, Yi Chen, et al.
Published: (2026)
by: Liu, Yi Chen, et al.
Published: (2026)
CLMIA: Membership Inference Attacks via Unsupervised Contrastive Learning
by: Chen, Depeng, et al.
Published: (2024)
by: Chen, Depeng, et al.
Published: (2024)
Hide in Plain Sight: Clean-Label Backdoor for Auditing Membership Inference
by: Chen, Depeng, et al.
Published: (2024)
by: Chen, Depeng, et al.
Published: (2024)
Explanations Leak: Membership Inference with Differential Privacy and Active Learning Defense
by: Ezzeddine, Fatima, et al.
Published: (2026)
by: Ezzeddine, Fatima, et al.
Published: (2026)
MCMC for Bayesian estimation of Differential Privacy from Membership Inference Attacks
by: Yildirim, Ceren, et al.
Published: (2025)
by: Yildirim, Ceren, et al.
Published: (2025)
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning
by: Sula, Nexhi, et al.
Published: (2024)
by: Sula, Nexhi, et al.
Published: (2024)
Model Agnostic Differentially Private Causal Inference
by: Lebeda, Christian Janos, et al.
Published: (2025)
by: Lebeda, Christian Janos, et al.
Published: (2025)
Tokens for Learning, Tokens for Unlearning: Mitigating Membership Inference Attacks in Large Language Models via Dual-Purpose Training
by: Tran, Toan, et al.
Published: (2025)
by: Tran, Toan, et al.
Published: (2025)
Cascading and Proxy Membership Inference Attacks
by: Du, Yuntao, et al.
Published: (2025)
by: Du, Yuntao, et al.
Published: (2025)
Differentially Private Non-convex Distributionally Robust Optimization
by: Xu, Difei, et al.
Published: (2026)
by: Xu, Difei, et al.
Published: (2026)
Nearly Optimal Differentially Private ReLU Regression
by: Ding, Meng, et al.
Published: (2025)
by: Ding, Meng, et al.
Published: (2025)
Better Membership Inference Privacy Measurement through Discrepancy
by: Wu, Ruihan, et al.
Published: (2024)
by: Wu, Ruihan, et al.
Published: (2024)
MRMMIA: Membership Inference Attacks on Memory in Chat Agents
by: Chen, Kai, et al.
Published: (2026)
by: Chen, Kai, et al.
Published: (2026)
(Token-Level) InfoRMIA: Stronger Membership Inference and Memorization Assessment for LLMs
by: Tao, Jiashu, et al.
Published: (2025)
by: Tao, Jiashu, et al.
Published: (2025)
Differentially Private Distributed Inference
by: Papachristou, Marios, et al.
Published: (2024)
by: Papachristou, Marios, et al.
Published: (2024)
Understanding the Impact of Differentially Private Training on Memorization of Long-Tailed Data
by: Zhang, Jiaming, et al.
Published: (2026)
by: Zhang, Jiaming, et al.
Published: (2026)
Noise-Aware Differentially Private Variational Inference
by: Alrawajfeh, Talal, et al.
Published: (2024)
by: Alrawajfeh, Talal, et al.
Published: (2024)
Finding Differentially Private Second Order Stationary Points in Stochastic Minimax Optimization
by: Xu, Difei, et al.
Published: (2026)
by: Xu, Difei, et al.
Published: (2026)
Optimal Differentially Private Model Training with Public Data
by: Lowy, Andrew, et al.
Published: (2023)
by: Lowy, Andrew, et al.
Published: (2023)
Differentially Private Sparse Linear Regression with Heavy-tailed Responses
by: Tian, Xizhi, et al.
Published: (2025)
by: Tian, Xizhi, et al.
Published: (2025)
Membership Inference Attacks as Privacy Tools: Reliability, Disparity and Ensemble
by: Wang, Zhiqi, et al.
Published: (2025)
by: Wang, Zhiqi, et al.
Published: (2025)
Bits for Privacy: Evaluating Post-Training Quantization via Membership Inference
by: Zhang, Chenxiang, et al.
Published: (2025)
by: Zhang, Chenxiang, et al.
Published: (2025)
Statistical Inference for Differentially Private Stochastic Gradient Descent
by: Xia, Xintao, et al.
Published: (2025)
by: Xia, Xintao, et al.
Published: (2025)
Differentially Private Covariate Balancing Causal Inference
by: Ohnishi, Yuki, et al.
Published: (2024)
by: Ohnishi, Yuki, et al.
Published: (2024)
Unveiling the Unseen: Exploring Whitebox Membership Inference through the Lens of Explainability
by: Li, Chenxi, et al.
Published: (2024)
by: Li, Chenxi, et al.
Published: (2024)
Similar Items
-
DP-aware AdaLN-Zero: Taming Conditioning-Induced Heavy-Tailed Gradients in Differentially Private Diffusion
by: Huang, Tao, et al.
Published: (2026) -
Intermediate Outputs Are More Sensitive Than You Think
by: Huang, Tao, et al.
Published: (2024) -
Enhancing DP-SGD through Non-monotonous Adaptive Scaling Gradient Weight
by: Huang, Tao, et al.
Published: (2024) -
Enhanced Privacy Leakage from Noise-Perturbed Gradients via Gradient-Guided Conditional Diffusion Models
by: Meng, Jiayang, et al.
Published: (2025) -
Real-Time Privacy Risk Measurement with Privacy Tokens for Gradient Leakage
by: Meng, Jiayang, et al.
Published: (2025)