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Machine Unlearning

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TitleStatusHype
Challenges and Pitfalls of Bayesian Unlearning—0
Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods—0
Are We Truly Forgetting? A Critical Re-examination of Machine Unlearning Evaluation Protocols—0
Erased but Not Forgotten: How Backdoors Compromise Concept Erasure—0
Adversarial Machine Unlearning—0
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning—0
Generative Adversarial Networks Unlearning—0
Enhancing User-Centric Privacy Protection: An Interactive Framework through Diffusion Models and Machine Unlearning—0
Eight Methods to Evaluate Robust Unlearning in LLMs—0
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning—0
Efficient Verified Machine Unlearning For Distillation—0
ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach—0
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity—0
Efficient and Generalizable Certified Unlearning: A Hessian-free Recollection Approach—0
A Review on Machine Unlearning—0
FROG: Fair Removal on Graphs—0
Efficient Machine Unlearning by Model Splitting and Core Sample Selection—0
Efficient Knowledge Deletion from Trained Models through Layer-wise Partial Machine Unlearning—0
Adapt then Unlearn: Exploiting Parameter Space Semantics for Unlearning in Generative Adversarial Networks—0
Exploring Fairness in Educational Data Mining in the Context of the Right to be Forgotten—0
Exploring Incremental Unlearning: Techniques, Challenges, and Future Directions—0
Exploring the Landscape of Machine Unlearning: A Comprehensive Survey and Taxonomy—0
Efficient Backdoor Defense in Multimodal Contrastive Learning: A Token-Level Unlearning Method for Mitigating Threats—0
Fairness and Robustness in Machine Unlearning—0
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage—0
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