"privacy preservation" Papers
27 papers found
Conference
An Inversion-based Measure of Memorization for Diffusion Models
Zhe Ma, Qingming Li, Xuhong Zhang et al.
Catastrophic Failure of LLM Unlearning via Quantization
Zhiwei Zhang, Fali Wang, Xiaomin Li et al.
CPSample: Classifier Protected Sampling for Guarding Training Data During Diffusion
Joshua Kazdan, Hao Sun, Jiaqi Han et al.
Curriculum Model Merging: Harmonizing Chemical LLMs for Enhanced Cross-Task Generalization
Baoyi He, Luotian Yuan, Ying Wei et al.
Diffusion Models for Attribution
Xiongren Chen, Jiuyong Li, Jixue Liu et al.
Does Training with Synthetic Data Truly Protect Privacy?
Yunpeng Zhao, Jie Zhang
EBS-CFL: Efficient and Byzantine-robust Secure Clustered Federated Learning
Zhiqiang Li, Haiyong Bao, Menghong Guan et al.
Edit Away and My Face Will not Stay: Personal Biometric Defense against Malicious Generative Editing
Hanhui Wang, Yihua Zhang, Ruizheng Bai et al.
FedAWA: Adaptive Optimization of Aggregation Weights in Federated Learning Using Client Vectors
Changlong Shi, He Zhao, Bingjie Zhang et al.
GC4NC: A Benchmark Framework for Graph Condensation on Node Classification with New Insights
Shengbo Gong, Juntong Ni, Noveen Sachdeva et al.
Know2Vec: A Black-Box Proxy for Neural Network Retrieval
Zhuoyi Shang, Yanwei Liu, Jinxia Liu et al.
Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research
A. Feder Cooper, Christopher A. Choquette-Choo, Miranda Bogen et al.
Medical Manifestation-Aware De-Identification
Yuan Tian, Shuo Wang, Guangtao Zhai
Memories of Forgotten Concepts
Matan Rusanovsky, Shimon Malnick, Amir Jevnisek et al.
OmniFC: Rethinking Federated Clustering via Lossless and Secure Distance Reconstruction
Jie Yan, Jing Liu, Zhong-Yuan Zhang
Prompt-based Unifying Inference Attack on Graph Neural Networks
Yuecen Wei, Xingcheng Fu, Lingyun Liu et al.
TimeDP: Learning to Generate Multi-Domain Time Series with Domain Prompts
Yu-Hao Huang, Chang Xu, Yueying Wu et al.
DecentNeRFs: Decentralized Neural Radiance Fields from Crowdsourced Images
Zaid Tasneem, Akshat Dave, Abhishek Singh et al.
Diffusion-Driven Data Replay: A Novel Approach to Combat Forgetting in Federated Class Continual Learning
Jinglin Liang, Jin Zhong, Hanlin Gu et al.
Feature Diversification and Adaptation for Federated Domain Generalization
Seunghan Yang, Seokeon Choi, Hyunsin Park et al.
FedVAD: Enhancing Federated Video Anomaly Detection with GPT-Driven Semantic Distillation
Fan Qi, Ruijie Pan, Huaiwen Zhang et al.
Leak and Learn: An Attacker's Cookbook to Train Using Leaked Data from Federated Learning
Joshua C. Zhao, Ahaan Dabholkar, Atul Sharma et al.
Non-exemplar Online Class-Incremental Continual Learning via Dual-Prototype Self-Augment and Refinement
Fushuo Huo, Wenchao Xu, Jingcai Guo et al.
PID: Prompt-Independent Data Protection Against Latent Diffusion Models
Ang Li, Yichuan Mo, Mingjie Li et al.
Real-Fake: Effective Training Data Synthesis Through Distribution Matching
Jianhao Yuan, Jie Zhang, Shuyang Sun et al.
Revisiting Gradient Pruning: A Dual Realization for Defending against Gradient Attacks
Lulu Xue, Shengshan Hu, Ruizhi Zhao et al.
To Each (Textual Sequence) Its Own: Improving Memorized-Data Unlearning in Large Language Models
George-Octavian Bărbulescu, Peter Triantafillou