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Machine Unlearning

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TitleStatusHype
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
Benchmarking Federated Machine Unlearning methods for Tabular Data—0
Prompting Forgetting: Unlearning in GANs via Textual Guidance—0
A Survey on Unlearnable DataCode1
Buyer-Initiated Auction Mechanism for Data Redemption in Machine Unlearning—0
Efficient Verified Machine Unlearning For Distillation—0
LoTUS: Large-Scale Machine Unlearning with a Taste of UncertaintyCode1
FROG: Fair Removal on Graphs—0
Deep Contrastive Unlearning for Language Models—0
Machine Unlearning in Hyperbolic vs. Euclidean Multimodal Contrastive Learning: Adapting Alignment Calibration to MERUCode0
Robust Machine Unlearning for Quantized Neural Networks via Adaptive Gradient Reweighting with Similar Labels—0
PEBench: A Fictitious Dataset to Benchmark Machine Unlearning for Multimodal Large Language Models—0
Safety Mirage: How Spurious Correlations Undermine VLM Safety Fine-tuningCode1
Group-robust Machine UnlearningCode0
Are We Truly Forgetting? A Critical Re-examination of Machine Unlearning Evaluation Protocols—0
Learning to Unlearn while Retaining: Combating Gradient Conflicts in Machine Unlearning—0
Node-level Contrastive Unlearning on Graph Neural Networks—0
AMUN: Adversarial Machine UNlearning—0
Data Unlearning in Diffusion ModelsCode1
Erasing Without Remembering: Implicit Knowledge Forgetting in Large Language ModelsCode1
SCU: An Efficient Machine Unlearning Scheme for Deep Learning Enabled Semantic CommunicationsCode0
TAPE: Tailored Posterior Difference for Auditing of Machine Unlearning—0
Holistic Audit Dataset Generation for LLM Unlearning via Knowledge Graph Traversal and Redundancy Removal—0
On the Vulnerability of Concept Erasure in Diffusion ModelsCode0
Forgetting Any Data at Any Time: A Theoretically Certified Unlearning Framework for Vertical Federated LearningCode0
When to Forget? Complexity Trade-offs in Machine Unlearning—0
Exploring Incremental Unlearning: Techniques, Challenges, and Future Directions—0
A Comprehensive Survey of Machine Unlearning Techniques for Large Language Models—0
Soft Token Attacks Cannot Reliably Audit Unlearning in Large Language Models—0
SafeEraser: Enhancing Safety in Multimodal Large Language Models through Multimodal Machine Unlearning—0
ReVeil: Unconstrained Concealed Backdoor Attack on Deep Neural Networks using Machine UnlearningCode0
MMUnlearner: Reformulating Multimodal Machine Unlearning in the Era of Multimodal Large Language ModelsCode1
Privacy Preservation through Practical Machine Unlearning—0
Comparative Study of Machine Unlearning Techniques for Computer Vision and NLP ModelsCode0
SEMU: Singular Value Decomposition for Efficient Machine Unlearning—0
Mitigating Sensitive Information Leakage in LLMs4Code through Machine Unlearning—0
Machine Unlearning via Information Theoretic Regularization—0
Realistic Image-to-Image Machine Unlearning via Decoupling and Knowledge Retention—0
FALCON: Fine-grained Activation Manipulation by Contrastive Orthogonal Unalignment for Large Language Model—0
Redefining Machine Unlearning: A Conformal Prediction-Motivated Approach—0
SAeUron: Interpretable Concept Unlearning in Diffusion Models with Sparse AutoencodersCode2
Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning—0
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning—0
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