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Machine Unlearning

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Showing 101–150 of 438 papers

TitleStatusHype
Learning to Forget using Hypernetworks—0
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
ERASER: Machine Unlearning in MLaaS via an Inference Serving-Aware Approach—0
Erased but Not Forgotten: How Backdoors Compromise Concept Erasure—0
Adversarial Machine Unlearning—0
Layer Attack Unlearning: Fast and Accurate Machine Unlearning via Layer Level Attack and Knowledge Distillation—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
Efficient Verified Machine Unlearning For Distillation—0
Efficient and Generalizable Certified Unlearning: A Hessian-free Recollection Approach—0
Certified Minimax Unlearning with Generalization Rates and Deletion Capacity—0
A Review on Machine Unlearning—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
Efficient Backdoor Defense in Multimodal Contrastive Learning: A Token-Level Unlearning Method for Mitigating Threats—0
Improved Localized Machine Unlearning Through the Lens of Memorization—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
Knowledge Unlearning for LLMs: Tasks, Methods, and Challenges—0
Fairness and Robustness in Machine Unlearning—0
Buyer-Initiated Auction Mechanism for Data Redemption in Machine Unlearning—0
Faster Machine Unlearning via Natural Gradient Descent—0
eCIL-MU: Embedding based Class Incremental Learning and Machine Unlearning—0
Controllable Unlearning for Image-to-Image Generative Models via -Constrained Optimization—0
An Introduction to Machine Unlearning—0
Holistic Audit Dataset Generation for LLM Unlearning via Knowledge Graph Traversal and Redundancy Removal—0
IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks—0
Bounding Membership Inference—0
Heterogeneous Decentralized Machine Unlearning with Seed Model Distillation—0
Does Machine Unlearning Truly Remove Model Knowledge? A Framework for Auditing Unlearning in LLMs—0
Boundary Unlearning: Rapid Forgetting of Deep Networks via Shifting the Decision Boundary—0
An Information Theoretic Evaluation Metric For Strong Unlearning—0
Label Smoothing Improves Machine Unlearning—0
Learning to Unlearn for Robust Machine Unlearning—0
Boundary Unlearning—0
Discriminative Adversarial Unlearning—0
MCU: Improving Machine Unlearning through Mode Connectivity—0
Digital Forgetting in Large Language Models: A Survey of Unlearning Methods—0
AND: Audio Network Dissection for Interpreting Deep Acoustic Models—0
GraphMU: Repairing Robustness of Graph Neural Networks via Machine Unlearning—0
Deletion Inference, Reconstruction, and Compliance in Machine (Un)Learning—0
A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models—0
Gradient Surgery for One-shot Unlearning on Generative Model—0
Deep Unlearn: Benchmarking Machine Unlearning—0
Benchmarking Federated Machine Unlearning methods for Tabular Data—0
DeepObliviate: A Powerful Charm for Erasing Data Residual Memory in Deep Neural Networks—0
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