Learning to Unlearn: Instance-wise Unlearning for Pre-trained Classifiers
Fuente:
arXiv
Saved in:
| Main Authors: | Cha, Sungmin, Cho, Sungjun, Hwang, Dasol, Lee, Honglak, Moon, Taesup, Lee, Moontae |
|---|---|
| Format: | Preprint |
| Published: |
2023
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs
by: Cha, Sungmin, et al.
Published: (2024)
by: Cha, Sungmin, et al.
Published: (2024)
Reference-Specific Unlearning Metrics Can Hide the Truth: A Reality Check
by: Cho, Sungjun, et al.
Published: (2025)
by: Cho, Sungjun, et al.
Published: (2025)
Towards Diverse Evaluation of Class Incremental Learning: A Representation Learning Perspective
by: Cha, Sungmin, et al.
Published: (2022)
by: Cha, Sungmin, et al.
Published: (2022)
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
by: Cha, Sungmin, et al.
Published: (2023)
by: Cha, Sungmin, et al.
Published: (2023)
Feature Unlearning for Pre-trained GANs and VAEs
by: Moon, Saemi, et al.
Published: (2023)
by: Moon, Saemi, et al.
Published: (2023)
Forget Forgetting: Continual Learning in a World of Abundant Memory
by: Cho, Dongkyu, et al.
Published: (2025)
by: Cho, Dongkyu, et al.
Published: (2025)
Towards Realistic Incremental Scenario in Class Incremental Semantic Segmentation
by: Kwak, Jihwan, et al.
Published: (2024)
by: Kwak, Jihwan, et al.
Published: (2024)
Knowledge Vector Weakening: Efficient Training-free Unlearning for Large Vision-Language Models
by: Kim, Yejin, et al.
Published: (2026)
by: Kim, Yejin, et al.
Published: (2026)
Unlearning the Unpromptable: Prompt-free Instance Unlearning in Diffusion Models
by: Lee, Kyungryeol, et al.
Published: (2026)
by: Lee, Kyungryeol, et al.
Published: (2026)
Are We Truly Forgetting? A Critical Re-examination of Machine Unlearning Evaluation Protocols
by: Kim, Yongwoo, et al.
Published: (2025)
by: Kim, Yongwoo, et al.
Published: (2025)
Pre-training for Recommendation Unlearning
by: Chen, Guoxuan, et al.
Published: (2025)
by: Chen, Guoxuan, et al.
Published: (2025)
Hyperparameters in Continual Learning: A Reality Check
by: Cha, Sungmin, et al.
Published: (2024)
by: Cha, Sungmin, et al.
Published: (2024)
Why Alignment Must Precede Distillation: A Minimal Working Explanation
by: Cha, Sungmin, et al.
Published: (2025)
by: Cha, Sungmin, et al.
Published: (2025)
Why Knowledge Distillation Works in Generative Models: A Minimal Working Explanation
by: Cha, Sungmin, et al.
Published: (2025)
by: Cha, Sungmin, et al.
Published: (2025)
Holistic Unlearning Benchmark: A Multi-Faceted Evaluation for Text-to-Image Diffusion Model Unlearning
by: Moon, Saemi, et al.
Published: (2024)
by: Moon, Saemi, et al.
Published: (2024)
Layer-wise Update Aggregation with Recycling for Communication-Efficient Federated Learning
by: Kim, Jisoo, et al.
Published: (2025)
by: Kim, Jisoo, et al.
Published: (2025)
Erase or Hide? Suppressing Spurious Unlearning Neurons for Robust Unlearning
by: Yang, Nakyeong, et al.
Published: (2025)
by: Yang, Nakyeong, et al.
Published: (2025)
Leveraging Per-Instance Privacy for Machine Unlearning
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2025)
by: Sepahvand, Nazanin Mohammadi, et al.
Published: (2025)
Erase at the Core: Representation Unlearning for Machine Unlearning
by: Lee, Jaewon, et al.
Published: (2026)
by: Lee, Jaewon, et al.
Published: (2026)
Machine Unlearning of Pre-trained Large Language Models
by: Yao, Jin, et al.
Published: (2024)
by: Yao, Jin, et al.
Published: (2024)
Contrastive Unlearning: A Contrastive Approach to Machine Unlearning
by: Lee, Hong kyu, et al.
Published: (2024)
by: Lee, Hong kyu, et al.
Published: (2024)
Instance-Level Difficulty: A Missing Perspective in Machine Unlearning
by: Rizwan, Hammad, et al.
Published: (2024)
by: Rizwan, Hammad, et al.
Published: (2024)
Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning
by: Kim, Seyeon, et al.
Published: (2024)
by: Kim, Seyeon, et al.
Published: (2024)
PiCa: Parameter-Efficient Fine-Tuning with Column Space Projection
by: Hwang, Junseo, et al.
Published: (2025)
by: Hwang, Junseo, et al.
Published: (2025)
Contrast-CAT: Contrasting Activations for Enhanced Interpretability in Transformer-based Text Classifiers
by: Han, Sungmin, et al.
Published: (2025)
by: Han, Sungmin, et al.
Published: (2025)
Concept Unlearning via Cross-Attention Activation Projection for Diffusion Models
by: Moon, Saemi, et al.
Published: (2026)
by: Moon, Saemi, et al.
Published: (2026)
Online Learning and Unlearning
by: Hu, Yaxi, et al.
Published: (2025)
by: Hu, Yaxi, et al.
Published: (2025)
Disentangled Sparse Representations for Concept-Separated Diffusion Unlearning
by: Kim, Hyeonjin, et al.
Published: (2026)
by: Kim, Hyeonjin, et al.
Published: (2026)
Sharpness-Aware Parameter Selection for Machine Unlearning
by: Malekmohammadi, Saber, et al.
Published: (2025)
by: Malekmohammadi, Saber, et al.
Published: (2025)
Controllable Machine Unlearning via Gradient Pivoting
by: Hwang, Youngsik, et al.
Published: (2025)
by: Hwang, Youngsik, et al.
Published: (2025)
FiCABU: A Fisher-Based, Context-Adaptive Machine Unlearning Processor for Edge AI
by: Cho, Eun-Su, et al.
Published: (2025)
by: Cho, Eun-Su, et al.
Published: (2025)
Targeted Unlearning with Single Layer Unlearning Gradient
by: Cai, Zikui, et al.
Published: (2024)
by: Cai, Zikui, et al.
Published: (2024)
Classifying Long-tailed and Label-noise Data via Disentangling and Unlearning
by: Shu, Chen, et al.
Published: (2025)
by: Shu, Chen, et al.
Published: (2025)
Routing by Reaching: Composition of Pre-trained GFlowNets for Multi-Objective Generation
by: Yoon, Seokwon, et al.
Published: (2026)
by: Yoon, Seokwon, et al.
Published: (2026)
Learning to Unlearn for Robust Machine Unlearning
by: Huang, Mark He, et al.
Published: (2024)
by: Huang, Mark He, et al.
Published: (2024)
Distillation Robustifies Unlearning
by: Lee, Bruce W., et al.
Published: (2025)
by: Lee, Bruce W., et al.
Published: (2025)
Class-wise Federated Unlearning: Harnessing Active Forgetting with Teacher-Student Memory Generation
by: Li, Yuyuan, et al.
Published: (2023)
by: Li, Yuyuan, et al.
Published: (2023)
An Unlearning Framework for Continual Learning
by: Adhikari, Sayanta, et al.
Published: (2025)
by: Adhikari, Sayanta, et al.
Published: (2025)
Machine Unlearning on Pre-trained Models by Residual Feature Alignment Using LoRA
by: Qin, Laiqiao, et al.
Published: (2024)
by: Qin, Laiqiao, et al.
Published: (2024)
Reset & Distill: A Recipe for Overcoming Negative Transfer in Continual Reinforcement Learning
by: Ahn, Hongjoon, et al.
Published: (2024)
by: Ahn, Hongjoon, et al.
Published: (2024)
Similar Items
-
Towards Robust and Parameter-Efficient Knowledge Unlearning for LLMs
by: Cha, Sungmin, et al.
Published: (2024) -
Reference-Specific Unlearning Metrics Can Hide the Truth: A Reality Check
by: Cho, Sungjun, et al.
Published: (2025) -
Towards Diverse Evaluation of Class Incremental Learning: A Representation Learning Perspective
by: Cha, Sungmin, et al.
Published: (2022) -
Regularizing with Pseudo-Negatives for Continual Self-Supervised Learning
by: Cha, Sungmin, et al.
Published: (2023) -
Feature Unlearning for Pre-trained GANs and VAEs
by: Moon, Saemi, et al.
Published: (2023)