CoreUnlearn: Rethinking Concept Unlearning through Disentangled Component-Level Erasure in Text-guided Diffusion Models
Fuente:
arXiv
Guardado en:
| Autores principales: | Zhao, Mengnan, Zhang, Lihe, Yin, Baocai |
|---|---|
| Formato: | Preprint |
| Publicado: |
2026
|
| Materias: | |
| Acceso en línea: | |
| Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
Catastrophic Overfitting: A Potential Blessing in Disguise
por: Zhao, Mengnan, et al.
Publicado: (2024)
por: Zhao, Mengnan, et al.
Publicado: (2024)
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
por: Zhang, Yimeng, et al.
Publicado: (2024)
por: Zhang, Yimeng, et al.
Publicado: (2024)
Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training
por: Zhao, Mengnan, et al.
Publicado: (2026)
por: Zhao, Mengnan, et al.
Publicado: (2026)
Rethinking Robust Adversarial Concept Erasure in Diffusion Models
por: Yin, Qinghong, et al.
Publicado: (2025)
por: Yin, Qinghong, et al.
Publicado: (2025)
Injection, Attack and Erasure: Revocable Backdoor Attacks via Machine Unlearning
por: Song, Baogang, et al.
Publicado: (2025)
por: Song, Baogang, et al.
Publicado: (2025)
Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts
por: Gao, Hongcheng, et al.
Publicado: (2024)
por: Gao, Hongcheng, et al.
Publicado: (2024)
Unlearn and Burn: Adversarial Machine Unlearning Requests Destroy Model Accuracy
por: Huang, Yangsibo, et al.
Publicado: (2024)
por: Huang, Yangsibo, et al.
Publicado: (2024)
Towards Irreversible Machine Unlearning for Diffusion Models
por: Yuan, Xun, et al.
Publicado: (2025)
por: Yuan, Xun, et al.
Publicado: (2025)
Learn What You Want to Unlearn: Unlearning Inversion Attacks against Machine Unlearning
por: Hu, Hongsheng, et al.
Publicado: (2024)
por: Hu, Hongsheng, et al.
Publicado: (2024)
Separable Multi-Concept Erasure from Diffusion Models
por: Zhao, Mengnan, et al.
Publicado: (2024)
por: Zhao, Mengnan, et al.
Publicado: (2024)
Don't Forget Too Much: Towards Machine Unlearning on Feature Level
por: Xu, Heng, et al.
Publicado: (2024)
por: Xu, Heng, et al.
Publicado: (2024)
Really Unlearned? Verifying Machine Unlearning via Influential Sample Pairs
por: Xu, Heng, et al.
Publicado: (2024)
por: Xu, Heng, et al.
Publicado: (2024)
Split Unlearning
por: Yu, Guangsheng, et al.
Publicado: (2023)
por: Yu, Guangsheng, et al.
Publicado: (2023)
Neighbor-Aware Localized Concept Erasure in Text-to-Image Diffusion Models
por: Shi, Zhuan, et al.
Publicado: (2026)
por: Shi, Zhuan, et al.
Publicado: (2026)
VideoEraser: Concept Erasure in Text-to-Video Diffusion Models
por: Xu, Naen, et al.
Publicado: (2025)
por: Xu, Naen, et al.
Publicado: (2025)
Unstable Unlearning: The Hidden Risk of Concept Resurgence in Diffusion Models
por: Suriyakumar, Vinith M., et al.
Publicado: (2024)
por: Suriyakumar, Vinith M., et al.
Publicado: (2024)
DUP: Detection-guided Unlearning for Backdoor Purification in Language Models
por: Hu, Man, et al.
Publicado: (2025)
por: Hu, Man, et al.
Publicado: (2025)
Jellyfish: Zero-Shot Federated Unlearning Scheme with Knowledge Disentanglement
por: Wang, Houzhe, et al.
Publicado: (2026)
por: Wang, Houzhe, et al.
Publicado: (2026)
Rethinking the Vulnerability of Concept Erasure and a New Method
por: Richardson, Alex D., et al.
Publicado: (2025)
por: Richardson, Alex D., et al.
Publicado: (2025)
Machine Unlearning in Large Language Models
por: Chen, Kongyang, et al.
Publicado: (2024)
por: Chen, Kongyang, et al.
Publicado: (2024)
AdvAnchor: Enhancing Diffusion Model Unlearning with Adversarial Anchors
por: Zhao, Mengnan, et al.
Publicado: (2024)
por: Zhao, Mengnan, et al.
Publicado: (2024)
Towards Efficient Target-Level Machine Unlearning Based on Essential Graph
por: Xu, Heng, et al.
Publicado: (2024)
por: Xu, Heng, et al.
Publicado: (2024)
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
por: Lee, Hong kyu, et al.
Publicado: (2024)
por: Lee, Hong kyu, et al.
Publicado: (2024)
Beyond Text Prompts: Precise Concept Erasure through Text-Image Collaboration
por: Li, Jun, et al.
Publicado: (2026)
por: Li, Jun, et al.
Publicado: (2026)
Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
por: Zhang, Jiahao, et al.
Publicado: (2026)
por: Zhang, Jiahao, et al.
Publicado: (2026)
KUDA: Knowledge Unlearning by Deviating Representation for Large Language Models
por: Fang, Ce, et al.
Publicado: (2026)
por: Fang, Ce, et al.
Publicado: (2026)
Rethinking Machine Unlearning in Image Generation Models
por: Liu, Renyang, et al.
Publicado: (2025)
por: Liu, Renyang, et al.
Publicado: (2025)
Unlearning Backdoor Attacks through Gradient-Based Model Pruning
por: Dunnett, Kealan, et al.
Publicado: (2024)
por: Dunnett, Kealan, et al.
Publicado: (2024)
Privacy Preservation through Practical Machine Unlearning
por: Dilworth, Robert
Publicado: (2025)
por: Dilworth, Robert
Publicado: (2025)
Reinforcement Unlearning
por: Ye, Dayong, et al.
Publicado: (2023)
por: Ye, Dayong, et al.
Publicado: (2023)
Label Inference Attacks against Federated Unlearning
por: Wang, Wei, et al.
Publicado: (2025)
por: Wang, Wei, et al.
Publicado: (2025)
BURN: Backdoor Unlearning via Adversarial Boundary Analysis
por: Su, Yanghao, et al.
Publicado: (2025)
por: Su, Yanghao, et al.
Publicado: (2025)
IMU: Influence-guided Machine Unlearning
por: Fan, Xindi, et al.
Publicado: (2025)
por: Fan, Xindi, et al.
Publicado: (2025)
FedMUA: Exploring the Vulnerabilities of Federated Learning to Malicious Unlearning Attacks
por: Chen, Jian, et al.
Publicado: (2025)
por: Chen, Jian, et al.
Publicado: (2025)
PDLRecover: Privacy-preserving Decentralized Model Recovery with Machine Unlearning
por: Li, Xiangman, et al.
Publicado: (2025)
por: Li, Xiangman, et al.
Publicado: (2025)
Verification of Machine Unlearning is Fragile
por: Zhang, Binchi, et al.
Publicado: (2024)
por: Zhang, Binchi, et al.
Publicado: (2024)
QUEEN: Query Unlearning against Model Extraction
por: Chen, Huajie, et al.
Publicado: (2024)
por: Chen, Huajie, et al.
Publicado: (2024)
On Large Language Model Continual Unlearning
por: Gao, Chongyang, et al.
Publicado: (2024)
por: Gao, Chongyang, et al.
Publicado: (2024)
Guaranteeing Data Privacy in Federated Unlearning with Dynamic User Participation
por: Liu, Ziyao, et al.
Publicado: (2024)
por: Liu, Ziyao, et al.
Publicado: (2024)
Verifiable Unlearning on Edge
por: Maheri, Mohammad M, et al.
Publicado: (2025)
por: Maheri, Mohammad M, et al.
Publicado: (2025)
Ejemplares similares
-
Catastrophic Overfitting: A Potential Blessing in Disguise
por: Zhao, Mengnan, et al.
Publicado: (2024) -
Defensive Unlearning with Adversarial Training for Robust Concept Erasure in Diffusion Models
por: Zhang, Yimeng, et al.
Publicado: (2024) -
Unveiling the Backdoor Mechanism Hidden Behind Catastrophic Overfitting in Fast Adversarial Training
por: Zhao, Mengnan, et al.
Publicado: (2026) -
Rethinking Robust Adversarial Concept Erasure in Diffusion Models
por: Yin, Qinghong, et al.
Publicado: (2025) -
Injection, Attack and Erasure: Revocable Backdoor Attacks via Machine Unlearning
por: Song, Baogang, et al.
Publicado: (2025)