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Machine Unlearning

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TitleStatusHype
Avoiding Copyright Infringement via Large Language Model UnlearningCode0
Towards Efficient Target-Level Machine Unlearning Based on Essential GraphCode0
RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language ModelsCode2
Recent Advances in Federated Learning Driven Large Language Models: A Survey on Architecture, Performance, and Security—0
Potion: Towards Poison UnlearningCode0
A More Practical Approach to Machine Unlearning—0
Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning—0
GENIU: A Restricted Data Access Unlearning for Imbalanced Data—0
Decoupling the Class Label and the Target Concept in Machine Unlearning—0
Label Smoothing Improves Machine Unlearning—0
Adversarial 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
What makes unlearning hard and what to do about itCode1
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
Automatic Jailbreaking of the Text-to-Image Generative AI SystemsCode1
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion ModelsCode2
Class Machine Unlearning for Complex Data via Concepts Inference and Data Poisoning—0
Machine Unlearning in Large Language ModelsCode1
Unlearning during Learning: An Efficient Federated Machine Unlearning MethodCode1
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