| Anonymizing Data for Privacy-Preserving Federated Learning | Feb 21, 2020 | BIG-bench Machine LearningFederated Learning | —Unverified | 0 |
| Deconvoluting Kernel Density Estimation and Regression for Locally Differentially Private Data | Aug 28, 2020 | Density EstimationPrivacy Preserving | —Unverified | 0 |
| Beyond the Federation: Topology-aware Federated Learning for Generalization to Unseen Clients | Jul 6, 2024 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| Beyond Text: Unveiling Privacy Vulnerabilities in Multi-modal Retrieval-Augmented Generation | May 20, 2025 | Privacy PreservingRAG | —Unverified | 0 |
| Anonymization Prompt Learning for Facial Privacy-Preserving Text-to-Image Generation | May 27, 2024 | Face SwappingImage Generation | —Unverified | 0 |
| Beyond Random Noise: Insights on Anonymization Strategies from a Latent Bandit Study | Sep 30, 2023 | Privacy Preserving | —Unverified | 0 |
| Towards the Anonymization of the Language Modeling | Jan 5, 2025 | Causal Language ModelingLanguage Modeling | —Unverified | 0 |
| A Comprehensive Study on Model Initialization Techniques Ensuring Efficient Federated Learning | Oct 31, 2023 | Federated LearningPrivacy Preserving | —Unverified | 0 |
| Bridging Privacy and Robustness for Trustworthy Machine Learning | Mar 25, 2024 | Bayesian InferencePrivacy Preserving | —Unverified | 0 |
| Beyond Inferring Class Representatives: User-Level Privacy Leakage From Federated Learning | Dec 3, 2018 | Edge-computingFederated Learning | —Unverified | 0 |
