:: Library Catalog

Imagen de Portada

Guardado en:

Detalles Bibliográficos
Autores principales:	Hu, Shengyuan, Fu, Yiwei, Wu, Zhiwei Steven, Smith, Virginia
Formato:	Preprint
Publicado:	2024
Materias:	Machine Learning
Acceso en línea:	https://arxiv.org/abs/2406.13356
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

Ejemplares similares

BLUR: A Benchmark for LLM Unlearning Robust to Forget-Retain Overlap
por: Hu, Shengyuan, et al.
Publicado: (2025)

Rethinking Benign Relearning: Syntax as the Hidden Driver of Unlearning Failures
por: Yoon, Sangyeon, et al.
Publicado: (2026)

Layered Unlearning for Adversarial Relearning
por: Qian, Timothy, et al.
Publicado: (2025)

Guardrail Baselines for Unlearning in LLMs
por: Thaker, Pratiksha, et al.
Publicado: (2024)

Meta-Unlearning on Diffusion Models: Preventing Relearning Unlearned Concepts
por: Gao, Hongcheng, et al.
Publicado: (2024)

Unlearning's Blind Spots: Over-Unlearning and Prototypical Relearning Attack
por: Ha, SeungBum, et al.
Publicado: (2025)

Efficient Unlearning through Maximizing Relearning Convergence Delay
por: Tran, Khoa, et al.
Publicado: (2026)

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

Unlearning Isn't Invisible: Detecting Unlearning Traces in LLMs from Model Outputs
por: Chen, Yiwei, et al.
Publicado: (2025)

COLUR: Confidence-Oriented Learning, Unlearning and Relearning with Noisy-Label Data for Model Restoration and Refinement
por: Sui, Zhihao, et al.
Publicado: (2025)

SAEs $\textit{Can}$ Improve Unlearning: Dynamic Sparse Autoencoder Guardrails for Precision Unlearning in LLMs
por: Muhamed, Aashiq, et al.
Publicado: (2025)

FedCARE: Federated Unlearning with Conflict-Aware Projection and Relearning-Resistant Recovery
por: Li, Yue, et al.
Publicado: (2026)

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

Unlearning vs. Obfuscation: Are We Truly Removing Knowledge?
por: Sun, Guangzhi, et al.
Publicado: (2025)

Position: LLM Unlearning Benchmarks are Weak Measures of Progress
por: Thaker, Pratiksha, et al.
Publicado: (2024)

Towards LLM Unlearning Resilient to Relearning Attacks: A Sharpness-Aware Minimization Perspective and Beyond
por: Fan, Chongyu, et al.
Publicado: (2025)

Exact Unlearning of Finetuning Data via Model Merging at Scale
por: Kuo, Kevin, et al.
Publicado: (2025)

Enhancing One-run Privacy Auditing with Quantile Regression-Based Membership Inference
por: Liu, Terrance, et al.
Publicado: (2025)

Unlearning Isn't Deletion: Investigating Reversibility of Machine Unlearning in LLMs
por: Xu, Xiaoyu, et al.
Publicado: (2025)

Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
por: Bertran, Martin, et al.
Publicado: (2024)

Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding
por: Reisizadeh, Hadi, et al.
Publicado: (2025)

DP2Unlearning: An Efficient and Guaranteed Unlearning Framework for LLMs
por: Mahmud, Tamim Al, et al.
Publicado: (2025)

FUNU: Boosting Machine Unlearning Efficiency by Filtering Unnecessary Unlearning
por: Li, Zitong, et al.
Publicado: (2025)

Unified Parameter-Efficient Unlearning for LLMs
por: Ding, Chenlu, et al.
Publicado: (2024)

Leverage Unlearning to Sanitize LLMs
por: Boutet, Antoine, et al.
Publicado: (2025)

Learning-Time Encoding Shapes Unlearning in LLMs
por: Wu, Ruihan, et al.
Publicado: (2025)

Online Learning and Unlearning
por: Hu, Yaxi, et al.
Publicado: (2025)

UCD: Unlearning in LLMs via Contrastive Decoding
por: Suriyakumar, Vinith M., et al.
Publicado: (2025)

Targeted Unlearning with Single Layer Unlearning Gradient
por: Cai, Zikui, et al.
Publicado: (2024)

Probing Knowledge Holes in Unlearned LLMs
por: Ko, Myeongseob, et al.
Publicado: (2025)

Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs
por: Kadhe, Swanand Ravindra, et al.
Publicado: (2024)

Mechanistic Unlearning: Robust Knowledge Unlearning and Editing via Mechanistic Localization
por: Guo, Phillip, et al.
Publicado: (2024)

How Data Inter-connectivity Shapes LLMs Unlearning: A Structural Unlearning Perspective
por: Qiu, Xinchi, et al.
Publicado: (2024)

Federated Graph Unlearning
por: Ai, Yuming, et al.
Publicado: (2025)

Unlearning through Knowledge Overwriting: Reversible Federated Unlearning via Selective Sparse Adapter
por: Zhong, Zhengyi, et al.
Publicado: (2025)

Tool Unlearning for Tool-Augmented LLMs
por: Cheng, Jiali, et al.
Publicado: (2025)

Align-then-Unlearn: Embedding Alignment for LLM Unlearning
por: Spohn, Philipp, et al.
Publicado: (2025)

Textual Unlearning Gives a False Sense of Unlearning
por: Du, Jiacheng, et al.
Publicado: (2024)

Does Unlearning Truly Unlearn? A Black Box Evaluation of LLM Unlearning Methods
por: Doshi, Jai, et al.
Publicado: (2024)

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