Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models

20 June 2024

Papers citing "Protecting Privacy Through Approximating Optimal Parameters for Sequence Unlearning in Language Models"

8 / 8 papers shown

Title
OBLIVIATE: Robust and Practical Machine Unlearning for Large Language Models Xiaoyu Xu Minxin Du Qingqing Ye Haibo Hu MU 57 0 0 07 May 2025
Breaking Chains: Unraveling the Links in Multi-Hop Knowledge Unlearning Minseok Choi C. Park Dohyun Lee Jaegul Choo KELM MU 31 1 0 17 Oct 2024
Cross-Lingual Unlearning of Selective Knowledge in Multilingual Language Models Minseok Choi Kyunghyun Min Jaegul Choo MU AAML 32 1 0 18 Jun 2024
Rethinking Machine Unlearning for Large Language Models Sijia Liu Yuanshun Yao Jinghan Jia Stephen Casper Nathalie Baracaldo ... Hang Li Kush R. Varshney Mohit Bansal Sanmi Koyejo Yang Liu AILaw MU 72 83 0 13 Feb 2024
Knowledge Unlearning for Mitigating Privacy Risks in Language Models Joel Jang Dongkeun Yoon Sohee Yang Sungmin Cha Moontae Lee Lajanugen Logeswaran Minjoon Seo KELM PILM MU 147 191 0 04 Oct 2022
Differentially Private Fine-tuning of Language Models Da Yu Saurabh Naik A. Backurs Sivakanth Gopi Huseyin A. Inan ... Y. Lee Andre Manoel Lukas Wutschitz Sergey Yekhanin Huishuai Zhang 134 347 0 13 Oct 2021
The Pile: An 800GB Dataset of Diverse Text for Language Modeling Leo Gao Stella Biderman Sid Black Laurence Golding Travis Hoppe ... Horace He Anish Thite Noa Nabeshima Shawn Presser Connor Leahy AIMat 259 1,996 0 31 Dec 2020
PubMedQA: A Dataset for Biomedical Research Question Answering Qiao Jin Bhuwan Dhingra Zhengping Liu William W. Cohen Xinghua Lu 219 812 0 13 Sep 2019