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Machine Unlearning

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Showing 326–350 of 438 papers

TitleStatusHype
Right to be Forgotten in the Era of Large Language Models: Implications, Challenges, and Solutions—0
RKLD: Reverse KL-Divergence-based Knowledge Distillation for Unlearning Personal Information in Large Language Models—0
Robust Machine Unlearning for Quantized Neural Networks via Adaptive Gradient Reweighting with Similar Labels—0
Benchmarking Federated Machine Unlearning methods for Tabular Data—0
SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs—0
PolicyCleanse: Backdoor Detection and Mitigation in Reinforcement Learning—0
SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning—0
SAFE: Machine Unlearning With Shard Graphs—0
Backdoor Defense with Machine Unlearning—0
SALAD: Systematic Assessment of Machine Unlearing on LLM-Aided Hardware Design—0
Exploiting Machine Unlearning for Backdoor Attacks in Deep Learning System—0
A Zest of LIME: Towards Architecture-Independent Model Distances—0
Zero-shot Class Unlearning via Layer-wise Relevance Analysis and Neuronal Path Perturbation—0
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models—0
Ready2Unlearn: A Learning-Time Approach for Preparing Models with Future Unlearning Readiness—0
Second-Order Information Matters: Revisiting Machine Unlearning for Large Language Models—0
SecureCut: Federated Gradient Boosting Decision Trees with Efficient Machine Unlearning—0
Selective Forgetting: Advancing Machine Unlearning Techniques and Evaluation in Language Models—0
SEMU: Singular Value Decomposition for Efficient Machine Unlearning—0
Separable Multi-Concept Erasure from Diffusion Models—0
SEPS: A Separability Measure for Robust Unlearning in LLMs—0
A unified PAC-Bayesian framework for machine unlearning via information risk minimization—0
Verifying Robust Unlearning: Probing Residual Knowledge in Unlearned Models—0
Sharpness-Aware Machine Unlearning—0
Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations—0
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