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Privacy Preserving

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TitleStatusHype
Activity Recognition on Avatar-Anonymized Datasets with Masked Differential Privacy—0
Data Obfuscation through Latent Space Projection (LSP) for Privacy-Preserving AI Governance: Case Studies in Medical Diagnosis and Finance Fraud Detection—0
UnStar: Unlearning with Self-Taught Anti-Sample Reasoning for LLMs—0
Network Inversion for Training-Like Data Reconstruction—0
Private, Efficient and Scalable Kernel Learning for Medical Image Analysis—0
TS-ACL: Closed-Form Solution for Time Series-oriented Continual Learning—0
Personalized Federated Learning with Adaptive Feature Aggregation and Knowledge Transfer—0
FedSpaLLM: Federated Pruning of Large Language Models—0
Investigating Effective Speaker Property Privacy Protection in Federated Learning for Speech Emotion Recognition—0
Privacy-Preserving Decentralized AI with Confidential Computing—0
First-Person Fairness in Chatbots—0
P4GCN: Vertical Federated Social Recommendation with Privacy-Preserving Two-Party Graph Convolution Network—0
DEeR: Deviation Eliminating and Noise Regulating for Privacy-preserving Federated Low-rank AdaptationCode0
FedCAP: Robust Federated Learning via Customized Aggregation and PersonalizationCode0
Privacy-Preserving Synthetically Augmented Knowledge Graphs with Semantic Utility—0
Position: On-Premises LLM Deployment Demands a Middle Path: Preserving Privacy Without Sacrificing Model ConfidentialityCode0
Backdoor Attack on Vertical Federated Graph Neural Network Learning—0
Data Quality Control in Federated Instruction-tuning of Large Language Models—0
Feasibility Analysis of Federated Neural Networks for Explainable Detection of Atrial Fibrillation—0
Model-based Large Language Model Customization as Service—0
CollabEdit: Towards Non-destructive Collaborative Knowledge EditingCode0
Power-Softmax: Towards Secure LLM Inference over Encrypted Data—0
Privacy-Preserving Optimal State Estimation with Low Complexity via Cramér-Rao Lower Bound Approach—0
Dynamic Fusion Strategies for Federated Multimodal Recommendations—0
Privately Learning from Graphs with Applications in Fine-tuning Large Language ModelsCode0
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