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Machine Unlearning

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Showing 101–150 of 438 papers

TitleStatusHype
Sharpness-Aware Machine Unlearning—0
UCD: Unlearning in LLMs via Contrastive Decoding—0
Prompt Attacks Reveal Superficial Knowledge Removal in Unlearning Methods—0
Apollo: A Posteriori Label-Only Membership Inference Attack Towards Machine UnlearningCode0
SoK: Machine Unlearning for Large Language Models—0
Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning CompletenessCode0
Quantifying Cross-Modality Memorization in Vision-Language Models—0
Towards Machine Unlearning for Paralinguistic Speech Processing—0
SALAD: Systematic Assessment of Machine Unlearing on LLM-Aided Hardware Design—0
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-TuningCode0
Speech Unlearning—0
Aligned but Blind: Alignment Increases Implicit Bias by Reducing Awareness of RaceCode0
Does Machine Unlearning Truly Remove Model Knowledge? A Framework for Auditing Unlearning in LLMs—0
Targeted Unlearning Using Perturbed Sign Gradient Methods With Applications On Medical Images—0
Leveraging Per-Instance Privacy for Machine Unlearning—0
Soft Weighted Machine Unlearning—0
Losing is for Cherishing: Data Valuation Based on Machine Unlearning and Shapley Value—0
UniErase: Unlearning Token as a Universal Erasure Primitive for Language ModelsCode0
DUSK: Do Not Unlearn Shared KnowledgeCode0
A Unified Gradient-based Framework for Task-agnostic Continual Learning-Unlearning—0
SEPS: A Separability Measure for Robust Unlearning in LLMs—0
Few-Shot Concept Unlearning with Low Rank Adaptation—0
TAIJI: MCP-based Multi-Modal Data Analytics on Data Lakes—0
Privacy-Aware Lifelong LearningCode0
MCU: Improving Machine Unlearning through Mode Connectivity—0
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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