SoK: Reducing the Vulnerability of Fine-tuned Language Models to Membership Inference Attacks
Authors: Guy Amit, Abigail Goldsteen, Ariel Farkash | Published: 2024-03-13
プライバシー保護手法
A Framework for Cost-Effective and Self-Adaptive LLM Shaking and Recovery Mechanism
Authors: Zhiyu Chen, Yu Li, Suochao Zhang, Jingbo Zhou, Jiwen Zhou, Chenfu Bao, Dianhai Yu | Published: 2024-03-12
DP-TabICL: In-Context Learning with Differentially Private Tabular Data
Authors: Alycia N. Carey, Karuna Bhaila, Kennedy Edemacu, Xintao Wu | Published: 2024-03-08
On Protecting the Data Privacy of Large Language Models (LLMs): A Survey
Authors: Biwei Yan, Kun Li, Minghui Xu, Yueyan Dong, Yue Zhang, Zhaochun Ren, Xiuzhen Cheng | Published: 2024-03-08 | Updated: 2024-03-14
Wildest Dreams: Reproducible Research in Privacy-preserving Neural Network Training
Authors: Tanveer Khan, Mindaugas Budzys, Khoa Nguyen, Antonis Michalas | Published: 2024-03-06
Inf2Guard: An Information-Theoretic Framework for Learning Privacy-Preserving Representations against Inference Attacks
Authors: Sayedeh Leila Noorbakhsh, Binghui Zhang, Yuan Hong, Binghui Wang | Published: 2024-03-04
Analysis of Privacy Leakage in Federated Large Language Models
Authors: Minh N. Vu, Truc Nguyen, Tre' R. Jeter, My T. Thai | Published: 2024-03-02
Defending Against Data Reconstruction Attacks in Federated Learning: An Information Theory Approach
Authors: Qi Tan, Qi Li, Yi Zhao, Zhuotao Liu, Xiaobing Guo, Ke Xu | Published: 2024-03-02
Differentially Private Knowledge Distillation via Synthetic Text Generation
Authors: James Flemings, Murali Annavaram | Published: 2024-03-01 | Updated: 2024-06-05
Shifted Interpolation for Differential Privacy
Authors: Jinho Bok, Weijie Su, Jason M. Altschuler | Published: 2024-03-01 | Updated: 2024-06-12