Split, Unlearn, Merge: Leveraging Data Attributes for More Effective
Unlearning in LLMs

Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs

17 June 2024

Praneet Adusumilli

Dennis Wei

Nathalie Baracaldo

ArXiv (abs)PDF HTML

Papers citing "Split, Unlearn, Merge: Leveraging Data Attributes for More Effective Unlearning in LLMs"

8 / 8 papers shown

Title
Mitigating Biases in Language Models via Bias Unlearning Dianqing Liu Yi Liu Guoqing Jin Zhendong Mao MU 23 0 0 30 Sep 2025
A Survey on Generative Model Unlearning: Fundamentals, Taxonomy, Evaluation, and Future Direction Xiaohua Feng Jiaming Zhang Fengyuan Yu C. Wang Li Zhang Kaixiang Li Yuyuan Li Chaochao Chen Jianwei Yin MU 106 1 0 26 Jul 2025
Ready2Unlearn: A Learning-Time Approach for Preparing Models with Future Unlearning Readiness Hanyu Duan Yi Yang Ahmed Abbasi Kar Yan Tam MU OnRL 141 0 0 16 May 2025
Layered Unlearning for Adversarial Relearning Timothy Qian Vinith Suriyakumar Ashia Wilson Dylan Hadfield-Menell MU 126 1 0 14 May 2025
Exact Unlearning of Finetuning Data via Model Merging at Scale Kevin Kuo Amrith Rajagopal Setlur Kartik Srinivas Aditi Raghunathan Virginia Smith MoMe CLL MU 147 8 0 06 Apr 2025
Simplicity Prevails: Rethinking Negative Preference Optimization for LLM Unlearning Chongyu Fan Jiancheng Liu Licong Lin Jinghan Jia Ruiqi Zhang Song Mei Sijia Liu MU 276 53 0 09 Oct 2024
An Adversarial Perspective on Machine Unlearning for AI Safety Jakub Łucki Boyi Wei Yangsibo Huang Peter Henderson F. Tramèr Javier Rando MU AAML 395 69 0 26 Sep 2024
Recent Advances in Attack and Defense Approaches of Large Language Models Jing Cui Yishi Xu Zhewei Huang Shuchang Zhou Jianbin Jiao Junge Zhang PILM AAML 217 7 0 05 Sep 2024

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