:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Zhang, Tian, Tong, Yujia, Dong, Junhao, Xu, Ke, Wang, Yuze, Yuan, Jingling
Format:	Preprint
Published:	2026
Subjects:	Machine Learning
Online Access:	https://arxiv.org/abs/2602.00567
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Robust Machine Unlearning for Quantized Neural Networks via Adaptive Gradient Reweighting with Similar Labels
by: Tong, Yujia, et al.
Published: (2025)

LetheViT: Selective Machine Unlearning for Vision Transformers via Attention-Guided Contrastive Learning
by: Tong, Yujia, et al.
Published: (2025)

SAU: Sparsity-Aware Unlearning for LLMs via Gradient Masking and Importance Redistribution
by: Wang, Yuze, et al.
Published: (2026)

Enhancing Quantization-Aware Training on Edge Devices via Relative Entropy Coreset Selection and Cascaded Layer Correction
by: Tong, Yujia, et al.
Published: (2025)

Does Compression Preserve Uncertainty? A Unified Benchmark for Quantized and Sparse LLMs via Conformal Prediction
by: Tong, Yujia, et al.
Published: (2026)

Machine Unlearning using Forgetting Neural Networks
by: Hatua, Amartya, et al.
Published: (2024)

Machine Unlearning for Streaming Forgetting
by: Shen, Shaofei, et al.
Published: (2025)

CUFG: Curriculum Unlearning Guided by the Forgetting Gradient
by: Miao, Jiaxing, et al.
Published: (2025)

Certified Signed Graph Unlearning
by: Zhao, Junpeng, et al.
Published: (2025)

Forgetting That Sticks: Quantization-Permanent Unlearning via Circuit Attribution
by: Sadhu, Saisab, et al.
Published: (2026)

Towards Certified Unlearning for Deep Neural Networks
by: Zhang, Binchi, et al.
Published: (2024)

LLM Unlearning via Loss Adjustment with Only Forget Data
by: Wang, Yaxuan, et al.
Published: (2024)

FG-OrIU: Towards Better Forgetting via Feature-Gradient Orthogonality for Incremental Unlearning
by: Feng, Qian, et al.
Published: (2026)

Forgetting Has Neighbors: Localized Collateral Forgetting in Machine Unlearning
by: Dolgova, Polina, et al.
Published: (2026)

Machine Unlearning under Retain-Forget Entanglement
by: Cheng, Jingpu, et al.
Published: (2026)

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

Forgetting Through Transforming: Enabling Federated Unlearning via Class-Aware Representation Transformation
by: Guo, Qi, et al.
Published: (2024)

Forgetting to Forget: Attention Sink as A Gateway for Backdooring LLM Unlearning
by: Shang, Bingqi, et al.
Published: (2025)

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

Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
by: Shen, Shaofei, et al.
Published: (2024)

Quantized Approximately Orthogonal Recurrent Neural Networks
by: Foucault, Armand, et al.
Published: (2024)

Attack by Unlearning: Unlearning-Induced Adversarial Attacks on Graph Neural Networks
by: Zhang, Jiahao, et al.
Published: (2026)

Representation Unlearning: Forgetting through Information Compression
by: Almudévar, Antonio, et al.
Published: (2026)

Conditional Uncertainty Quantification for Tensorized Topological Neural Networks
by: Wu, Yujia, et al.
Published: (2024)

Towards Reliable Forgetting: A Survey on Machine Unlearning Verification
by: Xue, Lulu, et al.
Published: (2025)

DFQ-ViT: Data-Free Quantization for Vision Transformers without Fine-tuning
by: Tong, Yujia, et al.
Published: (2025)

Is Gradient Ascent Really Necessary? Memorize to Forget for Machine Unlearning
by: Huang, Zhuo, et al.
Published: (2026)

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

OMPQ: Orthogonal Mixed Precision Quantization
by: Ma, Yuexiao, et al.
Published: (2021)

Towards Aligned Data Forgetting via Twin Machine Unlearning
by: Niu, Zhenxing, et al.
Published: (2025)

Forget and Explain: Transparent Verification of GNN Unlearning
by: Ahsan, Imran, et al.
Published: (2025)

IDEA: A Flexible Framework of Certified Unlearning for Graph Neural Networks
by: Dong, Yushun, et al.
Published: (2024)

Delayed Bottlenecking: Alleviating Forgetting in Pre-trained Graph Neural Networks
by: Zhao, Zhe, et al.
Published: (2024)

To Forget or Not? Towards Practical Knowledge Unlearning for Large Language Models
by: Tian, Bozhong, et al.
Published: (2024)

Last-Iterate Analyses of FTRL with the 1/2-Tsallis Entropy in Stochastic Bandits
by: Zhan, Jingxin, et al.
Published: (2025)

Forgetting to Witness: Efficient Federated Unlearning and Its Visible Evaluation
by: Wang, Houzhe, et al.
Published: (2026)

Reducing Storage of Pretrained Neural Networks by Rate-Constrained Quantization and Entropy Coding
by: Conzelmann, Alexander, et al.
Published: (2025)

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

Mitigating Privacy Risk via Forget Set-Free Unlearning
by: Newatia, Aviraj, et al.
Published: (2026)

System-Aware Unlearning Algorithms: Use Lesser, Forget Faster
by: Lu, Linda, et al.
Published: (2025)