{"total":250,"rows":[{"id":"2103.03279","title":"Remember What You Want to Forget: Algorithms for Machine Unlearning","created":"2021-03-04","cited_by_count":371,"area":"safety"},{"id":"2209.02299","title":"A Survey of Machine Unlearning","created":"2022-09-06","cited_by_count":312,"area":"safety"},{"id":"2310.10683","title":"Large Language Model Unlearning","created":"2023-10-14","cited_by_count":302,"area":"safety"},{"id":"2302.09880","title":"Towards Unbounded Machine Unlearning","created":"2023-02-20","cited_by_count":268,"area":"safety"},{"id":"2407.06460","title":"MUSE: Machine Unlearning Six-Way Evaluation for Language Models","created":"2024-07-08","cited_by_count":261,"area":"safety"},{"id":"2108.11577","title":"Machine Unlearning of Features and Labels","created":"2021-08-26","cited_by_count":229,"area":"safety"},{"id":"2310.07579","title":"In-Context Unlearning: Language Models as Few Shot Unlearners","created":"2023-10-11","cited_by_count":224,"area":"safety"},{"id":"2111.08947","title":"Fast Yet Effective Machine Unlearning","created":"2021-11-17","cited_by_count":217,"area":"safety"},{"id":"2304.04934","title":"Model Sparsity Can Simplify Machine Unlearning","created":"2023-04-11","cited_by_count":214,"area":"safety"},{"id":"2205.08096","title":"Can Bad Teaching Induce Forgetting? Unlearning in Deep Networks using an Incompetent Teacher","created":"2022-05-17","cited_by_count":194,"area":"safety"},{"id":"2106.04378","title":"Adaptive Machine Unlearning","created":"2021-06-08","cited_by_count":176,"area":"safety"},{"id":"2103.14991","title":"Graph Unlearning","created":"2021-03-27","cited_by_count":138,"area":"safety"},{"id":"2201.05629","title":"Zero-Shot Machine Unlearning","created":"2022-01-14","cited_by_count":133,"area":"safety"},{"id":"2102.13179","title":"Machine Unlearning via Algorithmic Stability","created":"2021-02-25","cited_by_count":130,"area":"safety"},{"id":"2203.07320","title":"The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining","created":"2022-03-14","cited_by_count":118,"area":"safety"},{"id":"2110.11794","title":"Federated Unlearning via Class-Discriminative Pruning","created":"2021-10-22","cited_by_count":115,"area":"safety"},{"id":"2207.05521","title":"Federated Unlearning: How to Efficiently Erase a Client in FL?","created":"2022-07-12","cited_by_count":95,"area":"safety"},{"id":"2308.07061","title":"Machine Unlearning: Solutions and Challenges","created":"2023-08-14","cited_by_count":93,"area":"safety"},{"id":"2204.07655","title":"Deep Unlearning via Randomized Conditionally Independent Hessians","created":"2022-04-15","cited_by_count":84,"area":"safety"},{"id":"2406.13356","title":"Unlearning or Obfuscating? Jogging the Memory of Unlearned LLMs via Benign Relearning","created":"2024-06-19","cited_by_count":84,"area":"safety"},{"id":"2403.01218","title":"Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of Privacy","created":"2024-03-02","cited_by_count":82,"area":"safety"},{"id":"2310.13828","title":"Nightshade: Prompt-Specific Poisoning Attacks on Text-to-Image Generative Models","created":"2023-10-20","cited_by_count":75,"area":"safety"},{"id":"2310.12560","title":"Fast Model Debias with Machine Unlearning","created":"2023-10-19","cited_by_count":72,"area":"safety"},{"id":"2410.02879","title":"Position: LLM Unlearning Benchmarks are Weak Measures of Progress","created":"2024-10-03","cited_by_count":63,"area":"safety"},{"id":"2210.08911","title":"Forget Unlearning: Towards True Data-Deletion in Machine Learning","created":"2022-10-17","cited_by_count":61,"area":"safety"},{"id":"2304.02835","title":"GIF: A General Graph Unlearning Strategy via Influence Function","created":"2023-04-06","cited_by_count":60,"area":"safety"},{"id":"2109.08266","title":"Hard to Forget: Poisoning Attacks on Certified Machine Unlearning","created":"2021-09-17","cited_by_count":52,"area":"safety"},{"id":"2401.06187","title":"Scissorhands: Scrub Data Influence via Connection Sensitivity in Networks","created":"2024-01-11","cited_by_count":52,"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":"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":"2404.03233","title":"Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning","created":"2024-04-04","cited_by_count":48,"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":"2409.19732","title":"Unified Gradient-Based Machine Unlearning with Remain Geometry Enhancement","created":"2024-09-29","cited_by_count":45,"area":"safety"},{"id":"2403.07362","title":"Challenging Forgets: Unveiling the Worst-Case Forget Sets in Machine Unlearning","created":"2024-03-12","cited_by_count":44,"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":"2106.15093","title":"Certifiable Machine Unlearning for Linear Models","created":"2021-06-29","cited_by_count":42,"area":"safety"},{"id":"2110.06904","title":"Poison Forensics: Traceback of Data Poisoning Attacks in Neural Networks","created":"2021-10-13","cited_by_count":40,"area":"safety"},{"id":"2209.12269","title":"Algorithms that Approximate Data Removal: New Results and Limitations","created":"2022-09-25","cited_by_count":40,"area":"safety"},{"id":"2208.10836","title":"Evaluating Machine Unlearning via Epistemic Uncertainty","created":"2022-08-23","cited_by_count":39,"area":"safety"},{"id":"2410.18057","title":"CLEAR: Character Unlearning in Textual and Visual Modalities","created":"2024-10-23","cited_by_count":39,"area":"safety"},{"id":"2504.10957","title":"When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers","created":"2025-04-15","cited_by_count":38,"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":"2405.07406","title":"Machine Unlearning: A Comprehensive Survey","created":"2024-05-13","cited_by_count":35,"area":"safety"},{"id":"2309.08230","title":"A Duty to Forget, a Right to be Assured? Exposing Vulnerabilities in Machine Unlearning Services","created":"2023-09-15","cited_by_count":34,"area":"safety"},{"id":"2210.08196","title":"Deep Regression Unlearning","created":"2022-10-15","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":"2408.00920","title":"Towards Certified Unlearning for Deep Neural Networks","created":"2024-08-01","cited_by_count":31,"area":"safety"},{"id":"2312.10336","title":"Certified Minimax Unlearning with Generalization Rates and Deletion Capacity","created":"2023-12-16","cited_by_count":29,"area":"safety"},{"id":"2402.14015","title":"Corrective Machine Unlearning","created":"2024-02-21","cited_by_count":29,"area":"safety"},{"id":"2304.13169","title":"SAFE: Machine Unlearning With Shard Graphs","created":"2023-04-25","cited_by_count":28,"area":"safety"},{"id":"2311.02240","title":"Towards Machine Unlearning Benchmarks: Forgetting the Personal Identities in Facial Recognition Systems","created":"2023-11-03","cited_by_count":28,"area":"safety"},{"id":"2406.16257","title":"Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning","created":"2024-06-24","cited_by_count":27,"area":"safety"},{"id":"2506.06985","title":"Certified Unlearning for Neural Networks","created":"2025-06-08","cited_by_count":27,"area":"safety"},{"id":"2307.14754","title":"Fair Machine Unlearning: Data Removal while Mitigating Disparities","created":"2023-07-27","cited_by_count":26,"area":"safety"},{"id":"2210.09126","title":"Verifiable and Provably Secure Machine Unlearning","created":"2022-10-17","cited_by_count":25,"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":"2202.03460","title":"Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning","created":"2022-02-07","cited_by_count":24,"area":"safety"},{"id":"2310.18574","title":"Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning","created":"2023-10-28","cited_by_count":22,"area":"safety"},{"id":"2408.00929","title":"Verification of Machine Unlearning is Fragile","created":"2024-08-01","cited_by_count":21,"area":"safety"},{"id":"2302.08990","title":"Efficiently Forgetting What You Have Learned in Graph Representation Learning via Projection","created":"2023-02-17","cited_by_count":20,"area":"safety"},{"id":"2311.12047","title":"MultiDelete for Multimodal Machine Unlearning","created":"2023-11-18","cited_by_count":20,"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":"2306.03558","title":"Machine Unlearning: A Survey","created":"2023-06-06","cited_by_count":19,"area":"safety"},{"id":"2409.09778","title":"Rewind-to-Delete: Certified Machine Unlearning for Nonconvex Functions","created":"2024-09-15","cited_by_count":19,"area":"safety"},{"id":"2211.11656","title":"SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization","created":"2022-11-21","cited_by_count":18,"area":"safety"},{"id":"2401.11018","title":"Communication Efficient and Provable Federated Unlearning","created":"2024-01-19","cited_by_count":18,"area":"safety"},{"id":"2404.12922","title":"Is Retain Set All You Need in Machine Unlearning? Restoring Performance of Unlearned Models with Out-Of-Distribution Images","created":"2024-04-19","cited_by_count":18,"area":"safety"},{"id":"2409.11844","title":"MEOW: MEMOry Supervised LLM Unlearning Via Inverted Facts","created":"2024-09-18","cited_by_count":18,"area":"safety"},{"id":"2410.23232","title":"Attribute-to-Delete: Machine Unlearning via Datamodel Matching","created":"2024-10-30","cited_by_count":18,"area":"safety"},{"id":"2202.13295","title":"Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations","created":"2022-02-27","cited_by_count":17,"area":"safety"},{"id":"2406.14796","title":"MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning","created":"2024-06-21","cited_by_count":17,"area":"safety"},{"id":"2411.15537","title":"MUNBa: Machine Unlearning via Nash Bargaining","created":"2024-11-23","cited_by_count":17,"area":"safety"},{"id":"2402.01401","title":"An Information Theoretic Approach to Machine Unlearning","created":"2024-02-02","cited_by_count":16,"area":"safety"},{"id":"2311.16136","title":"ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach","created":"2023-11-03","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":"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":"2412.06966","title":"Machine Unlearning Doesn't Do What You Think: Lessons for Generative AI Policy and Research","created":"2024-12-09","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":"2504.04626","title":"Exact Unlearning of Finetuning Data via Model Merging at Scale","created":"2025-04-06","cited_by_count":14,"area":"safety"},{"id":"2209.00939","title":"An Introduction to Machine Unlearning","created":"2022-09-02","cited_by_count":13,"area":"safety"},{"id":"2309.16173","title":"Distill to Delete: Unlearning in Graph Networks with Knowledge Distillation","created":"2023-09-28","cited_by_count":13,"area":"safety"},{"id":"2312.02052","title":"DUCK: Distance-based Unlearning via Centroid Kinematics","created":"2023-12-04","cited_by_count":13,"area":"safety"},{"id":"2402.15109","title":"Remaining-data-free Machine Unlearning by Suppressing Sample Contribution","created":"2024-02-23","cited_by_count":13,"area":"safety"},{"id":"2406.09325","title":"REVS: Unlearning Sensitive Information in Language Models via Rank Editing in the Vocabulary Space","created":"2024-06-13","cited_by_count":13,"area":"safety"},{"id":"2302.06676","title":"Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendations","created":"2023-02-13","cited_by_count":12,"area":"safety"},{"id":"2406.08288","title":"Decoupling the Class Label and the Target Concept in Machine Unlearning","created":"2024-06-12","cited_by_count":12,"area":"safety"},{"id":"2505.22310","title":"From Dormant to Deleted: Tamper-Resistant Unlearning Through Weight-Space Regularization","created":"2025-05-28","cited_by_count":12,"area":"safety"},{"id":"2509.26427","title":"Ascent Fails to Forget","created":"2025-09-30","cited_by_count":12,"area":"safety"},{"id":"2306.15744","title":"Ticketed Learning-Unlearning Schemes","created":"2023-06-27","cited_by_count":11,"area":"safety"},{"id":"2308.09881","title":"Generative Adversarial Networks Unlearning","created":"2023-08-19","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":"2405.17878","title":"An Information Theoretic Evaluation Metric For Strong Unlearning","created":"2024-05-28","cited_by_count":11,"area":"safety"},{"id":"2506.06278","title":"Distillation Robustifies Unlearning","created":"2025-06-06","cited_by_count":11,"area":"safety"},{"id":"2508.13650","title":"CRISP: Persistent Concept Unlearning via Sparse Autoencoders","created":"2025-08-19","cited_by_count":11,"area":"safety"},{"id":"2210.07876","title":"Control, Confidentiality, and the Right to be Forgotten","created":"2022-10-14","cited_by_count":10,"area":"safety"},{"id":"2307.11228","title":"From Adaptive Query Release to Machine Unlearning","created":"2023-07-20","cited_by_count":10,"area":"safety"},{"id":"2407.17710","title":"Revisiting Machine Unlearning with Dimensional Alignment","created":"2024-07-25","cited_by_count":10,"area":"safety"},{"id":"2505.04416","title":"OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models","created":"2025-05-07","cited_by_count":10,"area":"safety"},{"id":"2405.19211","title":"Gone but Not Forgotten: Improved Benchmarks for Machine Unlearning","created":"2024-05-29","cited_by_count":9,"area":"safety"},{"id":"2406.07698","title":"Label Smoothing Improves Machine Unlearning","created":"2024-06-11","cited_by_count":9,"area":"safety"}],"next_cursor":"100"}