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Machine Unlearning

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Showing 201–250 of 438 papers

TitleStatusHype
FALCON: Fine-grained Activation Manipulation by Contrastive Orthogonal Unalignment for Large Language Model—0
Faster Machine Unlearning via Natural Gradient Descent—0
Fast Model Debias with Machine Unlearning—0
Fast-NTK: Parameter-Efficient Unlearning for Large-Scale Models—0
Federated Knowledge Graph Unlearning via Diffusion Model—0
Federated Large Language Models: Feasibility, Robustness, Security and Future Directions—0
Recent Advances in Federated Learning Driven Large Language Models: A Survey on Architecture, Performance, and Security—0
Federated Learning with Blockchain-Enhanced Machine Unlearning: A Trustworthy Approach—0
Federated Unlearning for Human Activity Recognition—0
Federated Unlearning via Active Forgetting—0
Few-Shot Concept Unlearning with Low Rank Adaptation—0
Few-Shot Unlearning by Model Inversion—0
Forgetting Fast in Recommender Systems—0
Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage—0
Forget Unlearning: Towards True Data-Deletion in Machine Learning—0
FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning—0
FROG: Fair Removal on Graphs—0
From Adaptive Query Release to Machine Unlearning—0
From Machine Learning to Machine Unlearning: Complying with GDPR's Right to be Forgotten while Maintaining Business Value of Predictive Models—0
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning—0
Game-Theoretic Machine Unlearning: Mitigating Extra Privacy Leakage—0
Generative Adversarial Networks Unlearning—0
GENIU: A Restricted Data Access Unlearning for Imbalanced Data—0
Provable unlearning in topic modeling and downstream tasks—0
Pseudo-Probability Unlearning: Towards Efficient and Privacy-Preserving Machine Unlearning—0
Quantifying Cross-Modality Memorization in Vision-Language Models—0
Random Relabeling for Efficient Machine Unlearning—0
Realistic Image-to-Image Machine Unlearning via Decoupling and Knowledge Retention—0
Recalling The Forgotten Class Memberships: Unlearned Models Can Be Noisy Labelers to Leak Privacy—0
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable—0
Redefining Machine Unlearning: A Conformal Prediction-Motivated Approach—0
Releasing Malevolence from Benevolence: The Menace of Benign Data on Machine Unlearning—0
Remembering Everything Makes You Vulnerable: A Limelight on Machine Unlearning for Personalized Healthcare Sector—0
Remember What You Want to Forget: Algorithms for Machine Unlearning—0
Rethinking Machine Unlearning for Large Language Models—0
Revisiting Machine Unlearning with Dimensional Alignment—0
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
SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning—0
SAFE: Machine Unlearning With Shard Graphs—0
SALAD: Systematic Assessment of Machine Unlearing on LLM-Aided Hardware Design—0
Score Forgetting Distillation: A Swift, Data-Free Method for Machine Unlearning in Diffusion Models—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
Sharpness-Aware Machine Unlearning—0
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