Cover Image

Zero-Shot Machine Unlearning with Proxy Adversarial Data Generation

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Chen, Huiqiang, Zhu, Tianqing, Yu, Xin, Zhou, Wanlei
Format:	Preprint
Published:	2025
Subjects:	Machine Learning Artificial Intelligence
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Machine Unlearning via Null Space Calibration
by: Chen, Huiqiang, et al.
Published: (2024)

AFed: Algorithmic Fair Federated Learning
by: Chen, Huiqiang, et al.
Published: (2025)

Graph Unlearning: Efficient Node Removal in Graph Neural Networks
by: Guan, Faqian, et al.
Published: (2025)

Federated Learning with Blockchain-Enhanced Machine Unlearning: A Trustworthy Approach
by: Zuo, Xuhan, et al.
Published: (2024)

Class Machine Unlearning for Complex Data via Concepts Inference and Data Poisoning
by: Chang, Wenhan, et al.
Published: (2024)

Discriminative Adversarial Unlearning
by: Sharma, Rohan, et al.
Published: (2024)

Large Language Models for Link Stealing Attacks Against Graph Neural Networks
by: Guan, Faqian, et al.
Published: (2024)

ZeroUnlearn: Few-Shot Knowledge Unlearning in Large Language Models
by: Lin, Yujie, et al.
Published: (2026)

When Fairness Meets Privacy: Exploring Privacy Threats in Fair Binary Classifiers via Membership Inference Attacks
by: Tian, Huan, et al.
Published: (2023)

How Does a Deep Learning Model Architecture Impact Its Privacy? A Comprehensive Study of Privacy Attacks on CNNs and Transformers
by: Zhang, Guangsheng, et al.
Published: (2022)

Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA
by: Qin, Laiqiao, et al.
Published: (2024)

Towards Efficient Target-Level Machine Unlearning Based on Essential Graph
by: Xu, Heng, et al.
Published: (2024)

On the Limitations and Prospects of Machine Unlearning for Generative AI
by: Zhou, Shiji, et al.
Published: (2024)

Update Selective Parameters: Federated Machine Unlearning Based on Model Explanation
by: Xu, Heng, et al.
Published: (2024)

Provable Zero-Shot Generalization in Offline Reinforcement Learning
by: Wang, Zhiyong, et al.
Published: (2025)

Recent Advances in Federated Learning Driven Large Language Models: A Survey on Architecture, Performance, and Security
by: Qu, Youyang, et al.
Published: (2024)

Safe and Reliable Diffusion Models via Subspace Projection
by: Chen, Huiqiang, et al.
Published: (2025)

Data Augmentation Improves Machine Unlearning
by: Falcao, Andreza M. C., et al.
Published: (2025)

Towards Mitigating Excessive Forgetting in LLM Unlearning via Entanglement-Guidance with Proxy Constraint
by: Liu, Zhihao, et al.
Published: (2025)

Data Duplication: A Novel Multi-Purpose Attack Paradigm in Machine Unlearning
by: Ye, Dayong, et al.
Published: (2025)

Debiasing Machine Unlearning with Counterfactual Examples
by: Chen, Ziheng, et al.
Published: (2024)

Forgetting Similar Samples: Can Machine Unlearning Do it Better?
by: Xu, Heng, et al.
Published: (2026)

Machine Unlearning in Contrastive Learning
by: Wang, Zixin, et al.
Published: (2024)

Vertical Federated Unlearning via Backdoor Certification
by: Han, Mengde, et al.
Published: (2024)

Machine Unlearning of Traffic State Estimation and Prediction
by: Wang, Xin, et al.
Published: (2025)

Agentic Unlearning: When LLM Agent Meets Machine Unlearning
by: Wang, Bin, et al.
Published: (2026)

Efficient Utility-Preserving Machine Unlearning with Implicit Gradient Surgery
by: Zhou, Shiji, et al.
Published: (2025)

Zero-shot Class Unlearning via Layer-wise Relevance Analysis and Neuronal Path Perturbation
by: Chang, Wenhan, et al.
Published: (2024)

Zero-Shot Robustification of Zero-Shot Models
by: Adila, Dyah, et al.
Published: (2023)

One-Shot Machine Unlearning with Mnemonic Code
by: Yamashita, Tomoya, et al.
Published: (2023)

An Adversarial Perspective on Machine Unlearning for AI Safety
by: Łucki, Jakub, et al.
Published: (2024)

CSC: Turning the Adversary's Poison against Itself
by: Shi, Yuchen, et al.
Published: (2026)

Deep Unlearn: Benchmarking Machine Unlearning for Image Classification
by: Cadet, Xavier F., et al.
Published: (2024)

Feature-Selective Representation Misdirection for Machine Unlearning
by: Chen, Taozhao, et al.
Published: (2025)

Towards Aligned Data Removal via Twin Machine Unlearning
by: Ji, Haoxuan, et al.
Published: (2024)

Fair Machine Unlearning: Data Removal while Mitigating Disparities
by: Oesterling, Alex, et al.
Published: (2023)

Synthetic Forgetting without Access: A Few-shot Zero-glance Framework for Machine Unlearning
by: Song, Qipeng, et al.
Published: (2025)

How to Protect Models against Adversarial Unlearning?
by: Jasiorski, Patryk, et al.
Published: (2025)

ROKA: Robust Knowledge Unlearning against Adversaries
by: Shin, Jinmyeong, et al.
Published: (2026)

Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text
by: Hans, Abhimanyu, et al.
Published: (2024)