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Privacy Preserving

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Showing 251–300 of 2975 papers

TitleStatusHype
Defending Against Gradient Inversion Attacks for Biomedical Images via Learnable Data Perturbation—0
Prada: Black-Box LLM Adaptation with Private Data on Resource-Constrained Devices—0
Zero-Knowledge Federated Learning: A New Trustworthy and Privacy-Preserving Distributed Learning Paradigm—0
Anomaly-Flow: A Multi-domain Federated Generative Adversarial Network for Distributed Denial-of-Service DetectionCode1
MOSAIC: Generating Consistent, Privacy-Preserving Scenes from Multiple Depth Views in Multi-Room Environments—0
Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation—0
ExChanGeAI: An End-to-End Platform and Efficient Foundation Model for Electrocardiogram Analysis and Fine-tuning—0
GC-Fed: Gradient Centralized Federated Learning with Partial Client ParticipationCode0
Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs—0
Towards Privacy-Preserving Data-Driven Education: The Potential of Federated Learning—0
PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models—0
Efficient and Privacy-Preserved Link Prediction via Condensed GraphsCode0
Effective and Efficient Cross-City Traffic Knowledge Transfer: A Privacy-Preserving Perspective—0
PA-CFL: Privacy-Adaptive Clustered Federated Learning for Transformer-Based Sales Forecasting on Heterogeneous Retail Data—0
TFHE-Coder: Evaluating LLM-agentic Fully Homomorphic Encryption Code Generation—0
A Survey on Federated Fine-tuning of Large Language ModelsCode2
Research on Large Language Model Cross-Cloud Privacy Protection and Collaborative Training based on Federated Learning—0
PrivacyScalpel: Enhancing LLM Privacy via Interpretable Feature Intervention with Sparse Autoencoders—0
PluralLLM: Pluralistic Alignment in LLMs via Federated Learning—0
One-Shot Federated Unsupervised Domain Adaptation with Scaled Entropy Attention and Multi-Source Smoothed Pseudo Labeling—0
Exploring the Vulnerabilities of Federated Learning: A Deep Dive into Gradient Inversion AttacksCode1
Optimal Privacy-Preserving Distributed Median Consensus—0
Faithful and Privacy-Preserving Implementation of Average Consensus—0
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative ModelsCode0
Self-supervised Normality Learning and Divergence Vector-guided Model Merging for Zero-shot Congenital Heart Disease Detection in Fetal Ultrasound Videos—0
Open-Set Gait Recognition from Sparse mmWave Radar Point CloudsCode1
COMODO: Cross-Modal Video-to-IMU Distillation for Efficient Egocentric Human Activity RecognitionCode1
Split-n-Chain: Privacy-Preserving Multi-Node Split Learning with Blockchain-Based Auditability—0
SecureGS: Boosting the Security and Fidelity of 3D Gaussian Splatting Steganography—0
FedEM: A Privacy-Preserving Framework for Concurrent Utility Preservation in Federated Learning—0
Mitigating Memorization in LLMs using Activation Steering—0
A Survey on Tabular Data Generation: Utility, Alignment, Fidelity, Privacy, and Beyond—0
Encrypted Vector Similarity Computations Using Partially Homomorphic Encryption: Applications and Performance AnalysisCode2
Uncertainty-Aware Explainable Federated Learning—0
Exploring FMCW Radars and Feature Maps for Activity Recognition: A Benchmark Study—0
Algorithmic Data Minimization for Machine Learning over Internet-of-Things Data Streams—0
Federated Dynamic Modeling and Learning for Spatiotemporal Data Forecasting—0
KidneyTalk-open: No-code Deployment of a Private Large Language Model with Medical Documentation-Enhanced Knowledge Database for Kidney DiseaseCode0
Privacy Preserving and Robust Aggregation for Cross-Silo Federated Learning in Non-IID Settings—0
Incentivizing Multi-Tenant Split Federated Learning for Foundation Models at the Network Edge—0
Generalization in Federated Learning: A Conditional Mutual Information Framework—0
FedPalm: A General Federated Learning Framework for Closed- and Open-Set Palmprint VerificationCode0
Token-Level Privacy in Large Language Models—0
Privacy is All You Need: Revolutionizing Wearable Health Data with Advanced PETs—0
Knowledge Augmentation in Federation: Rethinking What Collaborative Learning Can Bring Back to Decentralized Data—0
Federated nnU-Net for Privacy-Preserving Medical Image SegmentationCode1
Privacy-Preserving Fair Synthetic Tabular Data—0
Federated Learning for Privacy-Preserving Feedforward Control in Multi-Agent SystemsCode0
A Lightweight and Secure Deep Learning Model for Privacy-Preserving Federated Learning in Intelligent EnterprisesCode0
SHADE-AD: An LLM-Based Framework for Synthesizing Activity Data of Alzheimer's Patients—0
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