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Machine Unlearning

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Showing 126–150 of 438 papers

TitleStatusHype
Ready2Unlearn: A Learning-Time Approach for Preparing Models with Future Unlearning Readiness—0
Layered Unlearning for Adversarial RelearningCode0
MUBox: A Critical Evaluation Framework of Deep Machine Unlearning—0
Mirror Mirror on the Wall, Have I Forgotten it All? A New Framework for Evaluating Machine Unlearning—0
Federated Large Language Models: Feasibility, Robustness, Security and Future Directions—0
Certified Data Removal Under High-dimensional SettingsCode0
Efficient Machine Unlearning by Model Splitting and Core Sample Selection—0
Unilogit: Robust Machine Unlearning for LLMs Using Uniform-Target Self-Distillation—0
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models—0
Memory-Efficient Distributed Unlearning—0
Erased but Not Forgotten: How Backdoors Compromise Concept Erasure—0
Verifying Robust Unlearning: Probing Residual Knowledge in Unlearned Models—0
Fairness and Robustness in Machine Unlearning—0
SHA256 at SemEval-2025 Task 4: Selective Amnesia -- Constrained Unlearning for Large Language Models via Knowledge IsolationCode0
When is Task Vector Provably Effective for Model Editing? A Generalization Analysis of Nonlinear Transformers—0
LLM Unlearning Reveals a Stronger-Than-Expected Coreset Effect in Current BenchmarksCode0
Preserving Privacy Without Compromising Accuracy: Machine Unlearning for Handwritten Text Recognition—0
SAEs Can Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs—0
Not All Data Are Unlearned EquallyCode0
Sky of Unlearning (SoUL): Rewiring Federated Machine Unlearning via Selective Pruning—0
Prompting Forgetting: Unlearning in GANs via Textual Guidance—0
Benchmarking Federated Machine Unlearning methods for Tabular Data—0
Buyer-Initiated Auction Mechanism for Data Redemption in Machine Unlearning—0
Efficient Verified Machine Unlearning For Distillation—0
FROG: Fair Removal on Graphs—0
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