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Machine Unlearning

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Showing 251–300 of 438 papers

TitleStatusHype
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks—0
Machine Unlearning using a Multi-GAN based Model—0
Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models—0
Revisiting Machine Unlearning with Dimensional Alignment—0
One-Shot Unlearning of Personal IdentitiesCode0
Learning to Unlearn for Robust Machine Unlearning—0
Faster Machine Unlearning via Natural Gradient Descent—0
Zero-Shot Class Unlearning in CLIP with Synthetic SamplesCode0
Machine Unlearning for Medical Imaging—0
Mitigating Backdoor Attacks using Activation-Guided Model Editing—0
Releasing Malevolence from Benevolence: The Menace of Benign Data on Machine Unlearning—0
Remembering Everything Makes You Vulnerable: A Limelight on Machine Unlearning for Personalized Healthcare Sector—0
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning—0
Machine Unlearning Fails to Remove Data Poisoning AttacksCode0
Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning—0
Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios—0
AND: Audio Network Dissection for Interpreting Deep Acoustic Models—0
PISTOL: Dataset Compilation Pipeline for Structural Unlearning of LLMs—0
Blind Baselines Beat Membership Inference Attacks for Foundation ModelsCode0
MU-Bench: A Multitask Multimodal Benchmark for Machine UnlearningCode0
On Newton's Method to Unlearn Neural Networks—0
Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models—0
Jogging the Memory of Unlearned LLMs Through Targeted Relearning AttacksCode0
Textual Unlearning Gives a False Sense of Unlearning—0
GraphMU: Repairing Robustness of Graph Neural Networks via Machine Unlearning—0
Mitigating Social Biases in Language Models through Unlearning—0
Cross-Lingual Unlearning of Selective Knowledge in Multilingual Language ModelsCode0
Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation—0
Opt-Out: Investigating Entity-Level Unlearning for Large Language Models via Optimal TransportCode0
Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs—0
Avoiding Copyright Infringement via Large Language Model UnlearningCode0
Towards Efficient Target-Level Machine Unlearning Based on Essential GraphCode0
Recent Advances in Federated Learning Driven Large Language Models: A Survey on Architecture, Performance, and Security—0
Potion: Towards Poison UnlearningCode0
Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning—0
A More Practical Approach to Machine Unlearning—0
Decoupling the Class Label and the Target Concept in Machine Unlearning—0
GENIU: A Restricted Data Access Unlearning for Imbalanced Data—0
Adversarial Machine Unlearning—0
Label Smoothing Improves Machine Unlearning—0
Machine Unlearning for Uplink Interference Cancellation—0
Alignment Calibration: Machine Unlearning for Contrastive Learning under Auditing—0
RKLD: Reverse KL-Divergence-based Knowledge Distillation for Unlearning Personal Information in Large Language Models—0
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable—0
Gone but Not Forgotten: Improved Benchmarks for Machine Unlearning—0
An Information Theoretic Evaluation Metric For Strong Unlearning—0
Federated Learning with Blockchain-Enhanced Machine Unlearning: A Trustworthy Approach—0
Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten—0
Erase to Enhance: Data-Efficient Machine Unlearning in MRI ReconstructionCode0
Class Machine Unlearning for Complex Data via Concepts Inference and Data Poisoning—0
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