Cover Image

Data Unlearning Beyond Uniform Forgetting via Diffusion Time and Frequency Selection

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Park, Jinseong, Park, Mijung
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence Cryptography and Security
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Unlearn to Relearn Backdoors: Deferred Backdoor Functionality Attacks on Deep Learning Models
by: Shin, Jeongjin, et al.
Published: (2024)

ACU: Analytic Continual Unlearning for Efficient and Exact Forgetting with Privacy Preservation
by: Tang, Jianheng, et al.
Published: (2025)

Data-Free Privacy-Preserving for LLMs via Model Inversion and Selective Unlearning
by: Zhou, Xinjie, et al.
Published: (2026)

Forget to Flourish: Leveraging Machine-Unlearning on Pretrained Language Models for Privacy Leakage
by: Rashid, Md Rafi Ur, et al.
Published: (2024)

A Cognac Shot To Forget Bad Memories: Corrective Unlearning for Graph Neural Networks
by: Kolipaka, Varshita, et al.
Published: (2024)

FIT to Forget: Robust Continual Unlearning for Large Language Models
by: Xu, Xiaoyu, et al.
Published: (2026)

Continual Learning with Strategic Selection and Forgetting for Network Intrusion Detection
by: Zhang, Xinchen, et al.
Published: (2024)

DP-LDMs: Differentially Private Latent Diffusion Models
by: Liu, Michael F., et al.
Published: (2023)

Fast Exact Unlearning for In-Context Learning Data for LLMs
by: Muresanu, Andrei I., et al.
Published: (2024)

Multi-Class Support Vector Machine with Differential Privacy
by: Park, Jinseong, et al.
Published: (2025)

Unlink to Unlearn: Simplifying Edge Unlearning in GNNs
by: Tan, Jiajun, et al.
Published: (2024)

Forgetting-MarI: LLM Unlearning via Marginal Information Regularization
by: Xu, Shizhou, et al.
Published: (2025)

Scalable Federated Unlearning via Isolated and Coded Sharding
by: Lin, Yijing, et al.
Published: (2024)

Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios
by: Huang, Tao, et al.
Published: (2024)

Learning to Forget using Hypernetworks
by: Rangel, Jose Miguel Lara, et al.
Published: (2024)

Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning
by: Dou, Xuhui, et al.
Published: (2026)

GraphToxin: Reconstructing Full Unlearned Graphs from Graph Unlearning
by: Song, Ying, et al.
Published: (2025)

Towards Lifecycle Unlearning Commitment Management: Measuring Sample-level Unlearning Completeness
by: Wang, Cheng-Long, et al.
Published: (2025)

Breaking the Trilemma of Privacy, Utility, Efficiency via Controllable Machine Unlearning
by: Liu, Zheyuan, et al.
Published: (2023)

Unlearned but Not Forgotten: Data Extraction after Exact Unlearning in LLM
by: Wu, Xiaoyu, et al.
Published: (2025)

Hierarchical Dual-Strategy Unlearning for Biomedical and Healthcare Intelligence Using Imperfect and Privacy-Sensitive Medical Data
by: Zhang, Yi, et al.
Published: (2025)

The Erasure Illusion: Stress-Testing the Generalization of LLM Forgetting Evaluation
by: Jia, Hengrui, et al.
Published: (2025)

Revisiting Backdoor Attacks on Time Series Classification in the Frequency Domain
by: Huang, Yuanmin, et al.
Published: (2025)

Unlearning Inversion Attacks for Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2025)

SoK: Unlearnability and Unlearning for Model Dememorization
by: Zhang, Mengying, et al.
Published: (2026)

Stateless Yet Not Forgetful: Implicit Memory as a Hidden Channel in LLMs
by: Salem, Ahmed, et al.
Published: (2026)

WARP: Weight Teleportation for Attack-Resilient Unlearning Protocols
by: Maheri, Mohammad M, et al.
Published: (2025)

In-Context Unlearning: Language Models as Few Shot Unlearners
by: Pawelczyk, Martin, et al.
Published: (2023)

LMEraser: Large Model Unlearning through Adaptive Prompt Tuning
by: Xu, Jie, et al.
Published: (2024)

BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
by: Liu, Yi, et al.
Published: (2024)

SPARD: Defending Harmful Fine-Tuning Attack via Safety Projection with Relevance-Diversity Data Selection
by: Chen, Shuhao, et al.
Published: (2026)

ZK-APEX: Zero-Knowledge Approximate Personalized Unlearning with Executable Proofs
by: Maheri, Mohammad M, et al.
Published: (2025)

SALAD: Systematic Assessment of Machine Unlearning on LLM-Aided Hardware Design
by: Wang, Zeng, et al.
Published: (2025)

FRAMU: Attention-based Machine Unlearning using Federated Reinforcement Learning
by: Shaik, Thanveer, et al.
Published: (2023)

Machine Unlearning Fails to Remove Data Poisoning Attacks
by: Pawelczyk, Martin, et al.
Published: (2024)

Oblivionis: A Lightweight Learning and Unlearning Framework for Federated Large Language Models
by: Zhang, Fuyao, et al.
Published: (2025)

PRUNE: A Patching Based Repair Framework for Certifiable Unlearning of Neural Networks
by: Li, Xuran, et al.
Published: (2025)

Beyond Data Privacy: New Privacy Risks for Large Language Models
by: Du, Yuntao, et al.
Published: (2025)

Recalling The Forgotten Class Memberships: Unlearned Models Can Be Noisy Labelers to Leak Privacy
by: Sui, Zhihao, et al.
Published: (2025)

PureGen: Universal Data Purification for Train-Time Poison Defense via Generative Model Dynamics
by: Bhat, Sunay, et al.
Published: (2024)