Co-occurring keywords · papers mentioning both
Papers
Fine-grained Pluggable Gradient Ascent for Knowledge Unlearning in Language Models
EMNLP 2024
Fuse to Forget: Bias Reduction and Selective Memorization through Model Fusion
EMNLP 2024
Generative Unlearning for Any Identity
CVPR 2024
Label-Agnostic Forgetting: A Supervision-Free Unlearning in Deep Models
ICLR 2024
Langevin Unlearning: A New Perspective of Noisy Gradient Descent for Machine Unlearning
NeurIPS 2024
Large Language Model Unlearning
NeurIPS 2024
Large Language Model Unlearning via Embedding-Corrupted Prompts
NeurIPS 2024
Layer Attack Unlearning: Fast and Accurate Machine Unlearning via Layer Level Attack and Knowledge Distillation
AAAI 2024
Learning to Unlearn: Instance-Wise Unlearning for Pre-trained Classifiers
AAAI 2024
Learn To Unlearn for Deep Neural Networks: Minimizing Unlearning Interference With Gradient Projection
WACV 2024
Machine Unlearning: Challenges in Data Quality and Access
IJCAI 2024
Machine Unlearning for Image-to-Image Generative Models
ICLR 2024
Machine Unlearning of Pre-trained Large Language Models
ACL 2024
Machine Unlearning via Null Space Calibration
IJCAI 2024
Making Harmful Behaviors Unlearnable for Large Language Models
ACL 2024
One-Shot Machine Unlearning with Mnemonic Code
ACML 2024
On the Generalization of Training-based ChatGPT Detection Methods
EMNLP 2024
Reconstruction Attacks on Machine Unlearning: Simple Models are Vulnerable
NeurIPS 2024
Rethinking Adversarial Robustness in the Context of the Right to be Forgotten
ICML 2024
Rethinking Evaluation Methods for Machine Unlearning
EMNLP 2024
Reversing the Forget-Retain Objectives: An Efficient LLM Unlearning Framework from Logit Difference
NeurIPS 2024
Revisiting Who’s Harry Potter: Towards Targeted Unlearning from a Causal Intervention Perspective
EMNLP 2024
RRL: Recommendation Reverse Learning
AAAI 2024
SalUn: Empowering Machine Unlearning via Gradient-based Weight Saliency in Both Image Classification and Generation
ICLR 2024
SIFU: Sequential Informed Federated Unlearning for Efficient and Provable Client Unlearning in Federated Optimization
AISTATS 2024