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Machine Unlearning

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Showing 301–350 of 438 papers

TitleStatusHype
When to Forget? Complexity Trade-offs in Machine Unlearning—0
Why Fine-Tuning Struggles with Forgetting in Machine Unlearning? Theoretical Insights and a Remedial Approach—0
Zero-shot Class Unlearning via Layer-wise Relevance Analysis and Neuronal Path Perturbation—0
Machine Unlearning: its nature, scope, and importance for a "delete culture"—0
An Investigation on Learning, Polluting, and Unlearning the Spam Emails for Lifelong Learning—0
Machine Unlearning: Linear Filtration for Logit-based Classifiers—0
Machine Unlearning Method Based On Projection Residual—0
Machine Unlearning Methodology base on Stochastic Teacher Network—0
Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA—0
Machine Unlearning reveals that the Gender-based Violence Victim Condition can be detected from Speech in a Speaker-Agnostic Setting—0
Machine Unlearning: Taxonomy, Metrics, Applications, Challenges, and Prospects—0
Machine unlearning through fine-grained model parameters perturbation—0
Machine Unlearning using a Multi-GAN based Model—0
Machine Unlearning using Forgetting Neural Networks—0
Machine Unlearning via Algorithmic Stability—0
Machine unlearning via GAN—0
Machine Unlearning via Information Theoretic Regularization—0
Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios—0
Making Recommender Systems Forget: Learning and Unlearning for Erasable Recommendation—0
Markov Chain Monte Carlo-Based Machine Unlearning: Unlearning What Needs to be Forgotten—0
Memory-Efficient Distributed Unlearning—0
Mirror Mirror on the Wall, Have I Forgotten it All? A New Framework for Evaluating Machine Unlearning—0
Mitigating Backdoor Attacks using Activation-Guided Model Editing—0
Mitigating Sensitive Information Leakage in LLMs4Code through Machine Unlearning—0
Mitigating Social Biases in Language Models through Unlearning—0
Model Integrity when Unlearning with T2I Diffusion Models—0
Moderating the Generalization of Score-based Generative Model—0
MUBox: A Critical Evaluation Framework of Deep Machine Unlearning—0
Multi-Class Unlearning for Image Classification via Weight Filtering—0
MUter: Machine Unlearning on Adversarially Trained Models—0
τ: Gradient-based and Task-Agnostic machine Unlearning—0
Privacy and Copyright Protection in Generative AI: A Lifecycle Perspective—0
Netflix and Forget: Efficient and Exact Machine Unlearning from Bi-linear Recommendations—0
Neural Corrective Machine Unranking—0
Node-level Contrastive Unlearning on Graph Neural Networks—0
Noise is All You Need: Private Second-Order Convergence of Noisy SGD—0
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models—0
On Newton's Method to Unlearn Neural Networks—0
On the Limitations and Prospects of Machine Unlearning for Generative AI—0
On the Necessity of Auditable Algorithmic Definitions for Machine Unlearning—0
On the Necessity of Output Distribution Reweighting for Effective Class Unlearning—0
OpenGU: A Comprehensive Benchmark for Graph Unlearning—0
Open Knowledge Base Canonicalization with Multi-task Unlearning—0
Open Problems in Machine Unlearning for AI Safety—0
Orthogonal Soft Pruning for Efficient Class Unlearning—0
Partially Blinded Unlearning: Class Unlearning for Deep Networks a Bayesian Perspective—0
PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models—0
Person De-reidentification: A Variation-guided Identity Shift Modeling—0
PISTOL: Dataset Compilation Pipeline for Structural Unlearning of LLMs—0
PolicyCleanse: Backdoor Detection and Mitigation for Competitive Reinforcement Learning—0
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