model privacy

AudiFair: Privacy-Preserving Framework for Auditing Fairness UAI 2026 Marshaled Learning: Bridging Large Neural Networks with Memory-Constrained Trusted Execution Environments in Federated Learning WACV 2026 Enhancing Model Privacy in Federated Learning with Random Masking and Quantization EMNLP 2025 FaithUn: Toward Faithful Forgetting in Language Models by Investigating the Interconnectedness of Knowledge EMNLP 2025 R-TOFU: Unlearning in Large Reasoning Models EMNLP 2025 SHA256 at SemEval-2025 Task 4: Selective Amnesia – Constrained Unlearning for Large Language Models via Knowledge Isolation SemEval 2025 Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models EMNLP 2025 The Illusion of Unlearning: The Unstable Nature of Machine Unlearning in Text-to-Image Diffusion Models CVPR 2025 Towards Reverse Engineering of Language Models: A Survey EMNLP 2025 Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning ICLR 2025 Unlearning vs. Obfuscation: Are We Truly Removing Knowledge? EMNLP 2025 Backdoor Attacks via Machine Unlearning AAAI 2024 Membership Inference Attack Using Self Influence Functions WACV 2024 OSLO: One-Shot Label-Only Membership Inference Attacks NeurIPS 2024 Privacy Evaluation Benchmarks for NLP Models EMNLP 2024 Promoting Data and Model Privacy in Federated Learning through Quantized LoRA EMNLP 2024 When Fairness Meets Privacy: Exploring Privacy Threats in Fair Binary Classifiers via Membership Inference Attacks IJCAI 2024 Does Label Differential Privacy Prevent Label Inference Attacks? AISTATS 2023 MPCViT: Searching for Accurate and Efficient MPC-Friendly Vision Transformer with Heterogeneous Attention ICCV 2023 On the Privacy Risks of Algorithmic Recourse AISTATS 2023 Privacy Assessment on Reconstructed Images: Are Existing Evaluation Metrics Faithful to Human Perception? NeurIPS 2023 Tunable Soft Prompts are Messengers in Federated Learning EMNLP 2023 Leveraging Adversarial Examples To Quantify Membership Information Leakage CVPR 2022 Measuring Data Leakage in Machine-Learning Models with Fisher Information (Extended Abstract) IJCAI 2022 Analyzing the Confidentiality of Undistillable Teachers in Knowledge Distillation NeurIPS 2021