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Machine Unlearning

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Showing 251–300 of 438 papers

TitleStatusHype
Silver Linings in the Shadows: Harnessing Membership Inference for Machine Unlearning—0
Single Image Unlearning: Efficient Machine Unlearning in Multimodal Large Language Models—0
Sky of Unlearning (SoUL): Rewiring Federated Machine Unlearning via Selective Pruning—0
Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models—0
Soft Weighted Machine Unlearning—0
A Survey on Federated Unlearning: Challenges and Opportunities—0
SoK: Machine Unlearning for Large Language Models—0
Speech Unlearning—0
Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs—0
Survey of Security and Data Attacks on Machine Unlearning In Financial and E-Commerce—0
TAIJI: MCP-based Multi-Modal Data Analytics on Data Lakes—0
TAPE: Tailored Posterior Difference for Auditing of Machine Unlearning—0
Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images—0
Textual Unlearning Gives a False Sense of Unlearning—0
The Frontier of Data Erasure: Machine Unlearning for Large Language Models—0
The Illusion of Unlearning: The Unstable Nature of Machine Unlearning in Text-to-Image Diffusion Models—0
The Right to be Forgotten in Federated Learning: An Efficient Realization with Rapid Retraining—0
The Utility and Complexity of in- and out-of-Distribution Machine Unlearning—0
Threats, Attacks, and Defenses in Machine Unlearning: A Survey—0
Tight Bounds for Machine Unlearning via Differential Privacy—0
To Be Forgotten or To Be Fair: Unveiling Fairness Implications of Machine Unlearning Methods—0
Towards Aligned Data Forgetting via Twin Machine Unlearning—0
Towards Aligned Data Removal via Twin Machine Unlearning—0
Toward Scalable Graph Unlearning: A Node Influence Maximization based Approach—0
Towards Independence Criterion in Machine Unlearning of Features and Labels—0
Towards Machine Unlearning for Paralinguistic Speech Processing—0
Towards Natural Machine Unlearning—0
Towards Reliable Empirical Machine Unlearning Evaluation: A Game-Theoretic View—0
Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning—0
Towards Source-Free Machine Unlearning—0
Towards Understanding the Feasibility of Machine Unlearning—0
TruVRF: Towards Triple-Granularity Verification on Machine Unlearning—0
UCD: Unlearning in LLMs via Contrastive Decoding—0
Unfolded Self-Reconstruction LSH: Towards Machine Unlearning in Approximate Nearest Neighbour Search—0
Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation—0
Unlearnable Algorithms for In-context Learning—0
Unlearning as multi-task optimization: A normalized gradient difference approach with an adaptive learning rate—0
Unlearning Information Bottleneck: Machine Unlearning of Systematic Patterns and Biases—0
Unlearning in- vs. out-of-distribution data in LLMs under gradient-based method—0
Unlearning Trojans in Large Language Models: A Comparison Between Natural Language and Source Code—0
Unlearning with Control: Assessing Real-world Utility for Large Language Model Unlearning—0
Unlearning with Fisher Masking—0
Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation—0
Verifiable Unlearning on Edge—0
Verifying Robust Unlearning: Probing Residual Knowledge in Unlearned Models—0
Efficient Attribute Unlearning: Towards Selective Removal of Input Attributes from Feature Representations—0
ViT-MUL: A Baseline Study on Recent Machine Unlearning Methods Applied to Vision Transformers—0
What Should LLMs Forget? Quantifying Personal Data in LLMs for Right-to-Be-Forgotten Requests—0
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers—0
When Machine Unlearning Meets Retrieval-Augmented Generation (RAG): Keep Secret or Forget Knowledge?—0
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