differential privacy

RewardDS: Privacy-Preserving Fine-Tuning for Large Language Models via Reward Driven Data Synthesis EMNLP 2025 Robust Utility-Preserving Text Anonymization Based on Large Language Models ACL 2025 SAP: Privacy-Preserving Fine-Tuning on Language Models with Split-and-Privatize Framework IJCAI 2025 Scaling Laws for Differentially Private Language Models ICML 2025 Scaling up the Banded Matrix Factorization Mechanism for Large Scale Differentially Private ML ICLR 2025 Sharper Bounds for Chebyshev Moment Matching, with Applications COLT 2025 Singular Subspace Perturbation Bounds via Rectangular Random Matrix Diffusions ICLR 2025 Temporal Heterogeneous Graph Generation with Privacy, Utility, and Efficiency ICLR 2025 The Last Iterate Advantage: Empirical Auditing and Principled Heuristic Analysis of Differentially Private SGD ICLR 2025 The Role of Randomness in Stability ICML 2025 Tighter Privacy Auditing of DP-SGD in the Hidden State Threat Model ICLR 2025 Towards hyperparameter-free optimization with differential privacy ICLR 2025 Trading Off Voting Axioms for Privacy UAI 2025 TVineSynth: A Truncated C-Vine Copula Generator of Synthetic Tabular Data to Balance Privacy and Utility AISTATS 2025 VAGUE‐Gate: Plug‐and‐Play Local‐Privacy Shield for Retrieval‐Augmented Generation IJCNLP 2025 With Privacy, Size Matters: On the Importance of Dataset Size in Differentially Private Text Rewriting IJCNLP 2025 pfl-research: simulation framework for accelerating research in Private Federated Learning NeurIPS 2024 A Bayesian Approach for Personalized Federated Learning in Heterogeneous Settings NeurIPS 2024 A Collocation-based Method for Addressing Challenges in Word-level Metric Differential Privacy ACL 2024 A Comparative Analysis of Word-Level Metric Differential Privacy: Benchmarking the Privacy-Utility Trade-off COLING 2024 Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences NeurIPS 2024 A Differentially Private Clustering Algorithm for Well-Clustered Graphs ICLR 2024 Adversarially Robust Dense-Sparse Tradeoffs via Heavy-Hitters NeurIPS 2024 A Hassle-free Algorithm for Strong Differential Privacy in Federated Learning Systems EMNLP 2024 A Huber Loss Minimization Approach to Mean Estimation under User-level Differential Privacy NeurIPS 2024