{"total":22,"rows":[{"id":"2302.00539","title":"Analyzing Leakage of Personally Identifiable Information in Language Models","created":"2023-02-01","cited_by_count":285,"area":"safety"},{"id":"2111.08440","title":"On the Importance of Difficulty Calibration in Membership Inference Attacks","created":"2021-11-15","cited_by_count":147,"area":"safety"},{"id":"2309.06746","title":"DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass","created":"2023-09-13","cited_by_count":67,"area":"safety"},{"id":"2310.00108","title":"Practical Membership Inference Attacks Against Large-Scale Multi-Modal Models: A Pilot Study","created":"2023-09-29","cited_by_count":38,"area":"safety"},{"id":"2209.06997","title":"M^4I: Multi-modal Models Membership Inference","created":"2022-09-15","cited_by_count":34,"area":"safety"},{"id":"2306.07273","title":"Gaussian Membership Inference Privacy","created":"2023-06-12","cited_by_count":21,"area":"safety"},{"id":"2412.09119","title":"The Utility and Complexity of in- and out-of-Distribution Machine Unlearning","created":"2024-12-12","cited_by_count":20,"area":"safety"},{"id":"2402.09477","title":"PANORAMIA: Privacy Auditing of Machine Learning Models without Retraining","created":"2024-02-12","cited_by_count":17,"area":"safety"},{"id":"2403.17105","title":"Certified Machine Unlearning via Noisy Stochastic Gradient Descent","created":"2024-03-25","cited_by_count":14,"area":"safety"},{"id":"2411.05743","title":"Free Record-Level Privacy Risk Evaluation Through Artifact-Based Methods","created":"2024-11-08","cited_by_count":7,"area":"safety"},{"id":"2310.03838","title":"Chameleon: Increasing Label-Only Membership Leakage with Adaptive Poisoning","created":"2023-10-05","cited_by_count":5,"area":"safety"},{"id":"2311.03865","title":"When Fairness Meets Privacy: Exploring Privacy Threats in Fair Binary Classifiers via Membership Inference Attacks","created":"2023-11-07","cited_by_count":5,"area":"safety"},{"id":"2404.11577","title":"A Reliable Cryptographic Framework for Empirical Machine Unlearning Evaluation","created":"2024-04-17","cited_by_count":5,"area":"safety"},{"id":"2407.02747","title":"Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature","created":"2024-07-03","cited_by_count":5,"area":"safety"},{"id":"2212.03334","title":"Pre-trained Encoders in Self-Supervised Learning Improve Secure and Privacy-preserving Supervised Learning","created":"2022-12-06","cited_by_count":4,"area":"safety"},{"id":"2410.06814","title":"Defending Membership Inference Attacks via Privacy-aware Sparsity Tuning","created":"2024-10-09","cited_by_count":4,"area":"safety"},{"id":"2604.21197","title":"Toward Efficient Membership Inference Attacks against Federated Large Language Models: A Projection Residual Approach","created":"2026-04-23","cited_by_count":3,"area":"safety"},{"id":"2502.06374","title":"Hyperparameters in Score-Based Membership Inference Attacks","created":"2025-02-10","cited_by_count":2,"area":"safety"},{"id":"2512.16126","title":"Dual-View Inference Attack: Machine Unlearning Amplifies Privacy Exposure","created":"2025-12-18","cited_by_count":1,"area":"safety"},{"id":"2605.27292","title":"Detectability in Diversity: Improved Canary Crafting for Privacy Auditing in One Run","created":"2026-05-26","cited_by_count":0,"area":"safety"},{"id":"2609.33136","title":"Leaky Students: Membership Inference against On-Policy Distillation","created":"2026-09-27","cited_by_count":0,"area":"safety"},{"id":"2610.09651","title":"Closed-Form Noise Calibration Against Membership Inference for Random-Allocation DP-SGD","created":"2026-10-07","cited_by_count":0,"area":"safety"}],"next_cursor":null}