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Machine Unlearning

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Showing 301–350 of 438 papers

TitleStatusHype
Towards Natural Machine Unlearning—0
Unlearning Information Bottleneck: Machine Unlearning of Systematic Patterns and Biases—0
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models—0
Data Selection for Transfer Unlearning—0
Machine Unlearning: A Comprehensive Survey—0
Machine Unlearning in Contrastive Learning—0
Machine Unlearning for Document ClassificationCode0
Debiasing Machine Unlearning with Counterfactual Examples—0
Machine Unlearning via Null Space CalibrationCode0
Privacy-Preserving Debiasing using Data Augmentation and Machine Unlearning—0
Is Retain Set All You Need in Machine Unlearning? Restoring Performance of Unlearned Models with Out-Of-Distribution ImagesCode0
Towards Reliable Empirical Machine Unlearning Evaluation: A Game-Theoretic View—0
LMEraser: Large Model Unlearning through Adaptive Prompt TuningCode0
Goldfish: An Efficient Federated Unlearning FrameworkCode0
Efficient and Generalizable Certified Unlearning: A Hessian-free Recollection Approach—0
Digital Forgetting in Large Language Models: A Survey of Unlearning Methods—0
Machine Unlearning for Traditional Models and Large Language Models: A Short Survey—0
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep ModelsCode0
CPR: Retrieval Augmented Generation for Copyright Protection—0
Certified Machine Unlearning via Noisy Stochastic Gradient DescentCode0
Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective—0
The Frontier of Data Erasure: Machine Unlearning for Large Language Models—0
τ: Gradient-based and Task-Agnostic machine Unlearning—0
Threats, Attacks, and Defenses in Machine Unlearning: A Survey—0
Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Approximate Unlearning Completeness—0
Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models—0
Federated Knowledge Graph Unlearning via Diffusion Model—0
SAP: Corrective Machine Unlearning with Scaled Activation Projection for Label Noise RobustnessCode0
Machine Unlearning: Taxonomy, Metrics, Applications, Challenges, and Prospects—0
Towards Independence Criterion in Machine Unlearning of Features and Labels—0
Efficient Knowledge Deletion from Trained Models through Layer-wise Partial Machine Unlearning—0
A Survey on Federated Unlearning: Challenges and Opportunities—0
Dissecting Language Models: Machine Unlearning via Selective PruningCode0
Inexact Unlearning Needs More Careful Evaluations to Avoid a False Sense of PrivacyCode0
Loss-Free Machine Unlearning—0
Eight Methods to Evaluate Robust Unlearning in LLMs—0
Remaining-data-free Machine Unlearning by Suppressing Sample Contribution—0
Deciphering the Impact of Pretraining Data on Large Language Models through Machine Unlearning—0
Rethinking Machine Unlearning for Large Language Models—0
Discriminative Adversarial Unlearning—0
Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models—0
Example-based Explanations for Random Forests using Machine Unlearning—0
ViT-MUL: A Baseline Study on Recent Machine Unlearning Methods Applied to Vision Transformers—0
Separable Multi-Concept Erasure from Diffusion Models—0
Unlearnable Algorithms for In-context Learning—0
Dataset Condensation Driven Machine UnlearningCode0
CaMU: Disentangling Causal Effects in Deep Model UnlearningCode0
Towards Effective and General Graph Unlearning via Mutual EvolutionCode0
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning—0
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine UnlearningCode0
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