Saved in:
| Main Authors: | Zhao, Xingjian, Amiri, Mohammad Mohammadi, Magdon-Ismail, Malik |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2604.13438 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
OFMU: Optimization-Driven Framework for Machine Unlearning
by: Asif, Sadia, et al.
Published: (2025)
by: Asif, Sadia, et al.
Published: (2025)
The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning
by: Wei, Yu, et al.
Published: (2023)
by: Wei, Yu, et al.
Published: (2023)
Statistical Roughness-Informed Machine Unlearning
by: Partohaghighi, Mohammad, et al.
Published: (2026)
by: Partohaghighi, Mohammad, et al.
Published: (2026)
MultiDelete for Multimodal Machine Unlearning
by: Cheng, Jiali, et al.
Published: (2023)
by: Cheng, Jiali, et al.
Published: (2023)
MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning
by: Cheng, Jiali, et al.
Published: (2024)
by: Cheng, Jiali, et al.
Published: (2024)
Speech Unlearning
by: Cheng, Jiali, et al.
Published: (2025)
by: Cheng, Jiali, et al.
Published: (2025)
Predicting Time Series of Networked Dynamical Systems without Knowing Topology
by: Ding, Yanna, et al.
Published: (2024)
by: Ding, Yanna, et al.
Published: (2024)
Deep Unlearn: Benchmarking Machine Unlearning for Image Classification
by: Cadet, Xavier F., et al.
Published: (2024)
by: Cadet, Xavier F., et al.
Published: (2024)
Understanding Machine Unlearning Through the Lens of Mode Connectivity
by: Cheng, Jiali, et al.
Published: (2025)
by: Cheng, Jiali, et al.
Published: (2025)
Distribution-Guided and Constrained Quantum Machine Unlearning
by: Malik, Nausherwan, et al.
Published: (2026)
by: Malik, Nausherwan, et al.
Published: (2026)
Consistent Causal Inference of Group Effects in Non-Targeted Trials with Finitely Many Effect Levels
by: Mavroudeas, Georgios, et al.
Published: (2025)
by: Mavroudeas, Georgios, et al.
Published: (2025)
Gauss-Newton Unlearning for the LLM Era
by: McKinney, Lev, et al.
Published: (2026)
by: McKinney, Lev, et al.
Published: (2026)
Tool Unlearning for Tool-Augmented LLMs
by: Cheng, Jiali, et al.
Published: (2025)
by: Cheng, Jiali, et al.
Published: (2025)
On Newton's Method to Unlearn Neural Networks
by: Bui, Nhung, et al.
Published: (2024)
by: Bui, Nhung, et al.
Published: (2024)
Leveraging Per-Instance Privacy for Machine Unlearning
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2025)
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2025)
Machine Unlearning for Streaming Forgetting
by: Shen, Shaofei, et al.
Published: (2025)
by: Shen, Shaofei, et al.
Published: (2025)
Data Selection for Transfer Unlearning
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2024)
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2024)
An Illusion of Unlearning? Assessing Machine Unlearning Through Internal Representations
by: Gao, Yichen, et al.
Published: (2026)
by: Gao, Yichen, et al.
Published: (2026)
FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning
by: Li, Zitong, et al.
Published: (2025)
by: Li, Zitong, et al.
Published: (2025)
Unlearning during Learning: An Efficient Federated Machine Unlearning Method
by: Gu, Hanlin, et al.
Published: (2024)
by: Gu, Hanlin, et al.
Published: (2024)
Erase at the Core: Representation Unlearning for Machine Unlearning
by: Lee, Jaewon, et al.
Published: (2026)
by: Lee, Jaewon, et al.
Published: (2026)
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
by: Lee, Hong kyu, et al.
Published: (2024)
by: Lee, Hong kyu, et al.
Published: (2024)
Remaining-data-free Machine Unlearning by Suppressing Sample Contribution
by: Cheng, Xinwen, et al.
Published: (2024)
by: Cheng, Xinwen, et al.
Published: (2024)
Learning to Unlearn for Robust Machine Unlearning
by: Huang, Mark He, et al.
Published: (2024)
by: Huang, Mark He, et al.
Published: (2024)
Verifying Machine Unlearning with Explainable AI
by: Vidal, Àlex Pujol, et al.
Published: (2024)
by: Vidal, Àlex Pujol, et al.
Published: (2024)
A Survey of Machine Unlearning
by: Nguyen, Thanh Tam, et al.
Published: (2022)
by: Nguyen, Thanh Tam, et al.
Published: (2022)
Unlearning the Unpromptable: Prompt-free Instance Unlearning in Diffusion Models
by: Lee, Kyungryeol, et al.
Published: (2026)
by: Lee, Kyungryeol, et al.
Published: (2026)
Adversarial Machine Unlearning
by: Di, Zonglin, et al.
Published: (2024)
by: Di, Zonglin, et al.
Published: (2024)
Agentic Unlearning: When LLM Agent Meets Machine Unlearning
by: Wang, Bin, et al.
Published: (2026)
by: Wang, Bin, et al.
Published: (2026)
Unlearning Information Bottleneck: Machine Unlearning of Systematic Patterns and Biases
by: Han, Ling, et al.
Published: (2024)
by: Han, Ling, et al.
Published: (2024)
Reference-Guided Machine Unlearning
by: Mirlach, Jonas, et al.
Published: (2026)
by: Mirlach, Jonas, et al.
Published: (2026)
Sharpness-Aware Machine Unlearning
by: Tang, Haoran, et al.
Published: (2025)
by: Tang, Haoran, et al.
Published: (2025)
Fairness and Robustness in Machine Unlearning
by: Tran, Khoa, et al.
Published: (2025)
by: Tran, Khoa, et al.
Published: (2025)
A Review on Machine Unlearning
by: Zhang, Haibo, et al.
Published: (2024)
by: Zhang, Haibo, et al.
Published: (2024)
Towards Natural Machine Unlearning
by: He, Zhengbao, et al.
Published: (2024)
by: He, Zhengbao, et al.
Published: (2024)
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
by: Fraboni, Yann, et al.
Published: (2022)
by: Fraboni, Yann, et al.
Published: (2022)
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
by: Chien, Eli, et al.
Published: (2024)
by: Chien, Eli, et al.
Published: (2024)
Learn while Unlearn: An Iterative Unlearning Framework for Generative Language Models
by: Tang, Haoyu, et al.
Published: (2024)
by: Tang, Haoyu, et al.
Published: (2024)
DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs
by: Mahmud, Tamim Al, et al.
Published: (2025)
by: Mahmud, Tamim Al, et al.
Published: (2025)
Machine Unlearning with Minimal Gradient Dependence for High Unlearning Ratios
by: Huang, Tao, et al.
Published: (2024)
by: Huang, Tao, et al.
Published: (2024)
Similar Items
-
OFMU: Optimization-Driven Framework for Machine Unlearning
by: Asif, Sadia, et al.
Published: (2025) -
The Normal Distributions Indistinguishability Spectrum and its Application to Privacy-Preserving Machine Learning
by: Wei, Yu, et al.
Published: (2023) -
Statistical Roughness-Informed Machine Unlearning
by: Partohaghighi, Mohammad, et al.
Published: (2026) -
MultiDelete for Multimodal Machine Unlearning
by: Cheng, Jiali, et al.
Published: (2023) -
MU-Bench: A Multitask Multimodal Benchmark for Machine Unlearning
by: Cheng, Jiali, et al.
Published: (2024)