{"total":127,"rows":[{"id":"2112.03570","title":"Membership Inference Attacks From First Principles","created":"2021-12-07","cited_by_count":878,"area":"safety"},{"id":"2103.07853","title":"Membership Inference Attacks on Machine Learning: A Survey","created":"2021-03-14","cited_by_count":321,"area":"safety"},{"id":"2305.18462","title":"Membership Inference Attacks against Language Models via Neighbourhood Comparison","created":"2023-05-29","cited_by_count":258,"area":"safety"},{"id":"2111.09679","title":"Enhanced Membership Inference Attacks against Machine Learning Models","created":"2021-11-18","cited_by_count":248,"area":"safety"},{"id":"2402.07841","title":"Do Membership Inference Attacks Work on Large Language Models?","created":"2024-02-12","cited_by_count":195,"area":"safety"},{"id":"2402.00888","title":"Security and Privacy Challenges of Large Language Models: A Survey","created":"2024-01-30","cited_by_count":186,"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":"2104.10706","title":"Dataset Inference: Ownership Resolution in Machine Learning","created":"2021-04-21","cited_by_count":116,"area":"safety"},{"id":"2312.03262","title":"Low-Cost High-Power Membership Inference Attacks","created":"2023-12-06","cited_by_count":107,"area":"safety"},{"id":"2208.14933","title":"Membership Inference Attacks by Exploiting Loss Trajectory","created":"2022-08-31","cited_by_count":101,"area":"safety"},{"id":"2102.02551","title":"ML-Doctor: Holistic Risk Assessment of Inference Attacks Against Machine Learning Models","created":"2021-02-04","cited_by_count":85,"area":"safety"},{"id":"2101.01341","title":"Practical Blind Membership Inference Attack via Differential Comparisons","created":"2021-01-05","cited_by_count":78,"area":"safety"},{"id":"2108.11023","title":"EncoderMI: Membership Inference against Pre-trained Encoders in Contrastive Learning","created":"2021-08-25","cited_by_count":73,"area":"safety"},{"id":"2301.11578","title":"Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers","created":"2023-01-27","cited_by_count":67,"area":"safety"},{"id":"2307.03694","title":"Scalable Membership Inference Attacks via Quantile Regression","created":"2023-07-07","cited_by_count":65,"area":"safety"},{"id":"2406.17975","title":"SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It)","created":"2024-06-25","cited_by_count":59,"area":"safety"},{"id":"2402.14904","title":"Watermarking Makes Language Models Radioactive","created":"2024-02-22","cited_by_count":58,"area":"safety"},{"id":"2109.08045","title":"Membership Inference Attacks Against Recommender Systems","created":"2021-09-16","cited_by_count":57,"area":"safety"},{"id":"2406.09073","title":"Are we making progress in unlearning? Findings from the first NeurIPS unlearning competition","created":"2024-06-13","cited_by_count":50,"area":"safety"},{"id":"2302.07225","title":"Bounding Training Data Reconstruction in DP-SGD","created":"2023-02-14","cited_by_count":46,"area":"safety"},{"id":"2210.10750","title":"Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries","created":"2022-10-19","cited_by_count":40,"area":"safety"},{"id":"2505.11953","title":"Exploring Criteria of Loss Reweighting to Enhance LLM Unlearning","created":"2025-05-17","cited_by_count":39,"area":"safety"},{"id":"2207.05801","title":"RelaxLoss: Defending Membership Inference Attacks without Losing Utility","created":"2022-07-12","cited_by_count":37,"area":"safety"},{"id":"2312.04095","title":"Learn to Unlearn for Deep Neural Networks: Minimizing Unlearning Interference with Gradient Projection","created":"2023-12-07","cited_by_count":37,"area":"safety"},{"id":"2502.18943","title":"Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models","created":"2025-02-26","cited_by_count":37,"area":"safety"},{"id":"2106.11384","title":"Membership Inference on Word Embedding and Beyond","created":"2021-06-21","cited_by_count":35,"area":"safety"},{"id":"2209.06997","title":"M^4I: Multi-modal Models Membership Inference","created":"2022-09-15","cited_by_count":34,"area":"safety"},{"id":"2211.00463","title":"Amplifying Membership Exposure via Data Poisoning","created":"2022-11-01","cited_by_count":34,"area":"safety"},{"id":"2303.03446","title":"Students Parrot Their Teachers: Membership Inference on Model Distillation","created":"2023-03-06","cited_by_count":33,"area":"safety"},{"id":"2211.05427","title":"On the Privacy Risks of Algorithmic Recourse","created":"2022-11-10","cited_by_count":32,"area":"safety"},{"id":"2411.11315","title":"A Review on Machine Unlearning","created":"2024-11-18","cited_by_count":32,"area":"safety"},{"id":"2103.07101","title":"On the (In)Feasibility of Attribute Inference Attacks on Machine Learning Models","created":"2021-03-12","cited_by_count":31,"area":"safety"},{"id":"2412.06157","title":"Membership Inference Attacks and Defenses in Federated Learning: A Survey","created":"2024-12-09","cited_by_count":31,"area":"safety"},{"id":"2403.09562","title":"PreCurious: How Innocent Pre-Trained Language Models Turn into Privacy Traps","created":"2024-03-14","cited_by_count":23,"area":"safety"},{"id":"2407.15098","title":"SeqMIA: Sequential-Metric Based Membership Inference Attack","created":"2024-07-21","cited_by_count":23,"area":"safety"},{"id":"2409.13745","title":"Context-Aware Membership Inference Attacks against Pre-trained Large Language Models","created":"2024-09-11","cited_by_count":22,"area":"safety"},{"id":"2306.07273","title":"Gaussian Membership Inference Privacy","created":"2023-06-12","cited_by_count":21,"area":"safety"},{"id":"2409.00426","title":"Is Difficulty Calibration All We Need? Towards More Practical Membership Inference Attacks","created":"2024-08-31","cited_by_count":21,"area":"safety"},{"id":"2205.13680","title":"Membership Inference Attack Using Self Influence Functions","created":"2022-05-26","cited_by_count":20,"area":"safety"},{"id":"2204.06106","title":"Optimal Membership Inference Bounds for Adaptive Composition of Sampled Gaussian Mechanisms","created":"2022-04-12","cited_by_count":19,"area":"safety"},{"id":"2205.14055","title":"A Blessing of Dimensionality in Membership Inference through Regularization","created":"2022-05-27","cited_by_count":18,"area":"safety"},{"id":"2407.17417","title":"Can Watermarking Large Language Models Prevent Copyrighted Text Generation and Hide Training Data?","created":"2024-07-24","cited_by_count":18,"area":"safety"},{"id":"2102.07762","title":"Membership Inference Attacks are Easier on Difficult Problems","created":"2021-02-15","cited_by_count":17,"area":"safety"},{"id":"2206.01349","title":"On the Privacy Properties of GAN-generated Samples","created":"2022-06-03","cited_by_count":17,"area":"safety"},{"id":"2209.08615","title":"Membership Inference Attacks and Generalization: A Causal Perspective","created":"2022-09-18","cited_by_count":17,"area":"safety"},{"id":"2208.10445","title":"Membership-Doctor: Comprehensive Assessment of Membership Inference Against Machine Learning Models","created":"2022-08-22","cited_by_count":16,"area":"safety"},{"id":"2202.12232","title":"Bounding Membership Inference","created":"2022-02-24","cited_by_count":15,"area":"safety"},{"id":"2401.10458","title":"Contrastive Unlearning: A Contrastive Approach to Machine Unlearning","created":"2024-01-19","cited_by_count":15,"area":"safety"},{"id":"2202.01243","title":"Parameters or Privacy: A Provable Tradeoff Between Overparameterization and Membership Inference","created":"2022-02-02","cited_by_count":14,"area":"safety"},{"id":"2403.02116","title":"Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks","created":"2024-03-04","cited_by_count":13,"area":"safety"},{"id":"2405.16978","title":"OSLO: One-Shot Label-Only Membership Inference Attacks","created":"2024-05-27","cited_by_count":13,"area":"safety"},{"id":"2402.06289","title":"FedMIA: An Effective Membership Inference Attack Exploiting \"All for One\" Principle in Federated Learning","created":"2024-02-09","cited_by_count":12,"area":"safety"},{"id":"2408.05131","title":"Range Membership Inference Attacks","created":"2024-08-09","cited_by_count":12,"area":"safety"},{"id":"2310.00222","title":"Source Inference Attacks: Beyond Membership Inference Attacks in Federated Learning","created":"2023-09-30","cited_by_count":11,"area":"safety"},{"id":"2105.05381","title":"Accuracy-Privacy Trade-off in Deep Ensemble: A Membership Inference Perspective","created":"2021-05-12","cited_by_count":10,"area":"safety"},{"id":"2406.11544","title":"Do Parameters Reveal More than Loss for Membership Inference?","created":"2024-06-17","cited_by_count":10,"area":"safety"},{"id":"2411.19876","title":"LUMIA: Linear probing for Unimodal and MultiModal Membership Inference Attacks leveraging internal LLM states","created":"2024-11-29","cited_by_count":10,"area":"safety"},{"id":"2406.07698","title":"Label Smoothing Improves Machine Unlearning","created":"2024-06-11","cited_by_count":9,"area":"safety"},{"id":"2102.03314","title":"On Utility and Privacy in Synthetic Genomic Data","created":"2021-02-05","cited_by_count":8,"area":"safety"},{"id":"2205.06986","title":"Evaluating Membership Inference Through Adversarial Robustness","created":"2022-05-14","cited_by_count":8,"area":"safety"},{"id":"2211.15918","title":"Similarity Distribution based Membership Inference Attack on Person Re-identification","created":"2022-11-29","cited_by_count":8,"area":"safety"},{"id":"2405.07562","title":"GLiRA: Black-Box Membership Inference Attack via Knowledge Distillation","created":"2024-05-13","cited_by_count":7,"area":"safety"},{"id":"2406.19395","title":"Dataset Size Recovery from LoRA Weights","created":"2024-06-27","cited_by_count":7,"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":"2601.02751","title":"Window-based Membership Inference Attacks Against Fine-tuned Large Language Models","created":"2026-01-06","cited_by_count":7,"area":"safety"},{"id":"2111.01363","title":"Knowledge Cross-Distillation for Membership Privacy","created":"2021-11-02","cited_by_count":6,"area":"safety"},{"id":"2402.05453","title":"Mitigating Privacy Risk in Membership Inference by Convex-Concave Loss","created":"2024-02-08","cited_by_count":6,"area":"safety"},{"id":"2506.05126","title":"Membership Inference Attacks on Sequence Models","created":"2025-06-05","cited_by_count":6,"area":"safety"},{"id":"2507.21412","title":"Cascading and Proxy Membership Inference Attacks","created":"2025-07-29","cited_by_count":6,"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":"2310.13786","title":"Fundamental Limits of Membership Inference Attacks on Machine Learning Models","created":"2023-10-20","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":"2407.02747","title":"Curvature Clues: Decoding Deep Learning Privacy with Input Loss Curvature","created":"2024-07-03","cited_by_count":5,"area":"safety"},{"id":"2409.14513","title":"Order of Magnitude Speedups for LLM Membership Inference","created":"2024-09-22","cited_by_count":5,"area":"safety"},{"id":"2505.24089","title":"Practical Bayes-Optimal Membership Inference Attacks","created":"2025-05-30","cited_by_count":5,"area":"safety"},{"id":"2203.02080","title":"An Efficient Subpopulation-based Membership Inference Attack","created":"2022-03-04","cited_by_count":4,"area":"safety"},{"id":"2401.00996","title":"Safety and Performance, Why Not Both? Bi-Objective Optimized Model Compression against Heterogeneous Attacks Toward AI Software Deployment","created":"2024-01-02","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":"2509.05350","title":"Ensembling Membership Inference Attacks Against Tabular Generative Models","created":"2025-09-02","cited_by_count":4,"area":"safety"},{"id":"2212.02701","title":"On the Discredibility of Membership Inference Attacks","created":"2022-12-06","cited_by_count":3,"area":"safety"},{"id":"2307.06123","title":"SoK: Comparing Different Membership Inference Attacks with a Comprehensive Benchmark","created":"2023-07-12","cited_by_count":3,"area":"safety"},{"id":"2502.06567","title":"Membership Inference Risks in Quantized Models: A Theoretical and Empirical Study","created":"2025-02-10","cited_by_count":3,"area":"safety"},{"id":"2502.09974","title":"Has My System Prompt Been Used? Large Language Model Prompt Membership Inference","created":"2025-02-14","cited_by_count":3,"area":"safety"},{"id":"2509.06796","title":"Imitative Membership Inference Attack","created":"2025-09-08","cited_by_count":3,"area":"safety"},{"id":"2510.05699","title":"Membership Inference Attacks on Tokenizers of Large Language Models","created":"2025-10-07","cited_by_count":3,"area":"safety"},{"id":"2603.07567","title":"Revisiting the LiRA Membership Inference Attack Under Realistic Assumptions","created":"2026-03-08","cited_by_count":3,"area":"safety"},{"id":"2210.16258","title":"On the Vulnerability of Data Points under Multiple Membership Inference Attacks and Target Models","created":"2022-10-28","cited_by_count":2,"area":"safety"},{"id":"2310.08015","title":"Why Train More? Effective and Efficient Membership Inference via Memorization","created":"2023-10-12","cited_by_count":2,"area":"safety"},{"id":"2401.04929","title":"Learning-Based Difficulty Calibration for Enhanced Membership Inference Attacks","created":"2024-01-10","cited_by_count":2,"area":"safety"},{"id":"2503.07482","title":"How does Bayesian Sampling help Membership Inference Attacks?","created":"2025-03-10","cited_by_count":2,"area":"safety"},{"id":"2510.10625","title":"ImpMIA: Leveraging Implicit Bias for Membership Inference Attack","created":"2025-10-12","cited_by_count":2,"area":"safety"},{"id":"2511.16792","title":"Membership Inference Attacks Beyond Overfitting","created":"2025-11-20","cited_by_count":2,"area":"safety"},{"id":"2602.02819","title":"Causal Evaluation of Membership Inference Attacks","created":"2026-02-02","cited_by_count":2,"area":"safety"},{"id":"2602.07126","title":"Finding Connections: Membership Inference Attacks for the Multi-Table Synthetic Data Setting","created":"2026-02-06","cited_by_count":2,"area":"safety"},{"id":"2302.14769","title":"Membership Inference Attack for Beluga Whales Discrimination","created":"2023-02-28","cited_by_count":1,"area":"safety"},{"id":"2404.07139","title":"Towards a Game-theoretic Understanding of Explanation-based Membership Inference Attacks","created":"2024-04-10","cited_by_count":1,"area":"safety"},{"id":"2407.17663","title":"Explaining the Model, Protecting Your Data: Revealing and Mitigating the Data Privacy Risks of Post-Hoc Model Explanations via Membership Inference","created":"2024-07-24","cited_by_count":1,"area":"safety"},{"id":"2504.16683","title":"MCMC for Bayesian estimation of Differential Privacy from Membership Inference Attacks","created":"2025-04-23","cited_by_count":1,"area":"safety"},{"id":"2507.23291","title":"Evaluating the Dynamics of Membership Privacy in Deep Learning","created":"2025-07-31","cited_by_count":1,"area":"safety"},{"id":"2508.06244","title":"Membership Inference Attack with Partial Features","created":"2025-08-08","cited_by_count":1,"area":"safety"}],"next_cursor":"100"}