{"total":61,"rows":[{"id":"2407.06460","title":"MUSE: Machine Unlearning Six-Way Evaluation for Language Models","created":"2024-07-08","cited_by_count":261,"area":"safety"},{"id":"2402.15159","title":"Machine Unlearning of Pre-trained Large Language Models","created":"2024-02-23","cited_by_count":119,"area":"safety"},{"id":"2305.06360","title":"Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy","created":"2023-05-10","cited_by_count":51,"area":"safety"},{"id":"2401.10371","title":"Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning","created":"2024-01-18","cited_by_count":49,"area":"safety"},{"id":"2402.00351","title":"Machine Unlearning for Image-to-Image Generative Models","created":"2024-02-01","cited_by_count":47,"area":"safety"},{"id":"2212.10717","title":"Hidden Poison: Machine Unlearning Enables Camouflaged Poisoning Attacks","created":"2022-12-21","cited_by_count":43,"area":"safety"},{"id":"2403.13682","title":"Threats, Attacks, and Defenses in Machine Unlearning: A Survey","created":"2024-03-20","cited_by_count":39,"area":"safety"},{"id":"2406.17216","title":"Machine Unlearning Fails to Remove Data Poisoning Attacks","created":"2024-06-25","cited_by_count":37,"area":"safety"},{"id":"2304.13169","title":"SAFE: Machine Unlearning With Shard Graphs","created":"2023-04-25","cited_by_count":28,"area":"safety"},{"id":"2402.05947","title":"Separable Multi-Concept Erasure from Diffusion Models","created":"2024-02-03","cited_by_count":28,"area":"diffusion"},{"id":"2506.06985","title":"Certified Unlearning for Neural Networks","created":"2025-06-08","cited_by_count":27,"area":"safety"},{"id":"2405.20272","title":"Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable","created":"2024-05-30","cited_by_count":25,"area":"safety"},{"id":"2408.11071","title":"DiffZOO: A Purely Query-Based Black-Box Attack for Red-teaming Text-to-Image Generative Model via Zeroth Order Optimization","created":"2024-08-18","cited_by_count":22,"area":"diffusion"},{"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":"2407.10494","title":"Learning to Unlearn for Robust Machine Unlearning","created":"2024-07-15","cited_by_count":19,"area":"safety"},{"id":"2308.01937","title":"Training Data Protection with Compositional Diffusion Models","created":"2023-08-02","cited_by_count":17,"area":"diffusion"},{"id":"2406.06186","title":"A Survey on Machine Unlearning: Techniques and New Emerged Privacy Risks","created":"2024-06-10","cited_by_count":15,"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":"2306.15744","title":"Ticketed Learning-Unlearning Schemes","created":"2023-06-27","cited_by_count":11,"area":"safety"},{"id":"2309.14054","title":"Adapt then Unlearn: Exploring Parameter Space Semantics for Unlearning in Generative Adversarial Networks","created":"2023-09-25","cited_by_count":11,"area":"safety"},{"id":"2506.06112","title":"Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness","created":"2025-06-06","cited_by_count":11,"area":"safety"},{"id":"2506.06278","title":"Distillation Robustifies Unlearning","created":"2025-06-06","cited_by_count":11,"area":"safety"},{"id":"2502.17323","title":"When to Forget? Complexity Trade-offs in Machine Unlearning","created":"2025-02-24","cited_by_count":9,"area":"safety"},{"id":"2506.13009","title":"Rectifying Privacy and Efficacy Measurements in Machine Unlearning: A New Inference Attack Perspective","created":"2025-06-16","cited_by_count":9,"area":"safety"},{"id":"2403.12830","title":"Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Approximate Unlearning Completeness","created":"2024-03-19","cited_by_count":6,"area":"safety"},{"id":"2505.08576","title":"MUBox: A Critical Evaluation Framework of Deep Machine Unlearning","created":"2025-05-13","cited_by_count":6,"area":"safety"},{"id":"2312.14923","title":"Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models","created":"2023-12-22","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":"2502.19982","title":"Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language Models","created":"2025-02-27","cited_by_count":5,"area":"safety"},{"id":"2507.15112","title":"Distributional Machine Unlearning via Selective Data Removal","created":"2025-07-20","cited_by_count":5,"area":"safety"},{"id":"2505.22601","title":"Machine Unlearning under Overparameterization","created":"2025-05-28","cited_by_count":4,"area":"safety"},{"id":"2506.06073","title":"System-Aware Unlearning Algorithms: Use Lesser, Forget Faster","created":"2025-06-06","cited_by_count":4,"area":"safety"},{"id":"2601.22359","title":"The Unseen Threat: Residual Knowledge in Machine Unlearning under Perturbed Samples","created":"2026-01-29","cited_by_count":4,"area":"safety"},{"id":"2602.16697","title":"Protecting the Undeleted in Machine Unlearning","created":"2026-02-18","cited_by_count":4,"area":"safety"},{"id":"2604.15166","title":"Class Unlearning via Depth-Aware Removal of Forget-Specific Directions","created":"2026-04-16","cited_by_count":4,"area":"safety"},{"id":"2403.16246","title":"Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective","created":"2024-03-24","cited_by_count":3,"area":"safety"},{"id":"2404.03180","title":"Goldfish: An Efficient Federated Unlearning Framework","created":"2024-04-04","cited_by_count":3,"area":"safety"},{"id":"2306.12609","title":"Towards Regulatable AI Systems: Technical Gaps and Policy Opportunities","created":"2023-06-22","cited_by_count":2,"area":null},{"id":"2405.15517","title":"Erase to Enhance: Data-Efficient Machine Unlearning in MRI Reconstruction","created":"2024-05-24","cited_by_count":2,"area":"safety"},{"id":"2410.09311","title":"Data Deletion for Linear Regression with Noisy SGD","created":"2024-10-12","cited_by_count":2,"area":null},{"id":"2507.07754","title":"One-Point Contraction: Erasing Representational Separability toward Irreversible Deep Forgetting","created":"2025-07-10","cited_by_count":2,"area":"safety"},{"id":"2505.11270","title":"TAIJI: MCP-based Multi-Modal Data Analytics on Data Lakes","created":"2025-05-16","cited_by_count":1,"area":null},{"id":"2506.09923","title":"Apollo: A Posteriori Label-Only Membership Inference Attack Towards Machine Unlearning","created":"2025-06-11","cited_by_count":1,"area":"safety"},{"id":"2507.04771","title":"Efficient Unlearning with Privacy Guarantees","created":"2025-07-07","cited_by_count":1,"area":"safety"},{"id":"2509.12958","title":"Forget What's Sensitive, Remember What Matters: Token-Level Differential Privacy in Memory Sculpting for Continual Learning","created":"2025-09-16","cited_by_count":1,"area":null},{"id":"2512.08443","title":"Fully Decentralized Certified Unlearning","created":"2025-12-09","cited_by_count":1,"area":"safety"},{"id":"2603.03172","title":"Less Noise, Same Certificate: Retain Sensitivity for Unlearning","created":"2026-03-03","cited_by_count":1,"area":"safety"},{"id":"2604.04030","title":"Jellyfish: Zero-Shot Federated Unlearning Scheme with Knowledge Disentanglement","created":"2026-04-05","cited_by_count":1,"area":"safety"},{"id":"2605.16645","title":"Statistical Unlearning of Distributions: A Hypothesis Testing Approach","created":"2026-05-15","cited_by_count":1,"area":"safety"},{"id":"2606.26036","title":"Detect, Unlearn, Restore: Defending Text Summarization Models Against Data Poisoning","created":"2026-06-24","cited_by_count":1,"area":"safety"},{"id":"2607.05898","title":"Auditing of Unlearning Algorithms","created":"2026-07-07","cited_by_count":1,"area":"safety"},{"id":"2411.03914","title":"Game-Theoretic Machine Unlearning: Mitigating Extra Privacy Leakage","created":"2024-11-06","cited_by_count":0,"area":"safety"},{"id":"2507.15280","title":"Machine Unlearning for Streaming Forgetting","created":"2025-07-21","cited_by_count":0,"area":"safety"},{"id":"2511.15983","title":"Descend or Rewind? Stochastic Gradient Descent Unlearning","created":"2025-11-20","cited_by_count":0,"area":"safety"},{"id":"2602.14938","title":"Variance-Reduced $(\\varepsilon,\\delta)-$Unlearning using Forget Set Gradients","created":"2026-02-16","cited_by_count":0,"area":"safety"},{"id":"2604.04800","title":"Forgetting to Witness: Efficient Federated Unlearning and Its Visible Evaluation","created":"2026-04-06","cited_by_count":0,"area":"safety"},{"id":"2605.02297","title":"Graph Federated Unlearning for Privacy Preservation","created":"2026-05-04","cited_by_count":0,"area":"safety"},{"id":"2606.05804","title":"Can LLMs Be Constrained to the Past? Improving Knowledge Cutoff through Recall-Based Prompting","created":"2026-06-04","cited_by_count":0,"area":null},{"id":"2606.14518","title":"Characterizing Privacy-Audit Alignment in Behavioral Audit of Machine Unlearning","created":"2026-06-12","cited_by_count":0,"area":"safety"},{"id":"2610.04310","title":"Modeling Deletion Requests in Machine Unlearning","created":"2026-10-03","cited_by_count":0,"area":"safety"},{"id":"2610.17993","title":"Counterfactual Certification for Sequential Unlearning with Long-Run Performance Guarantees","created":"2026-10-13","cited_by_count":0,"area":"safety"}],"next_cursor":null}