How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing

20 May 2022

Papers citing "How to keep text private? A systematic review of deep learning methods for privacy-preserving natural language processing"

6 / 6 papers shown

Title
A Catalog of Fairness-Aware Practices in Machine Learning Engineering Gianmario Voria Giulia Sellitto Carmine Ferrara Francesco Abate A. Lucia F. Ferrucci Gemma Catolino Fabio Palomba FaML 39 3 0 29 Aug 2024
Recovering from Privacy-Preserving Masking with Large Language Models A. Vats Zhe Liu Peng Su Debjyoti Paul Yingyi Ma Yutong Pang Zeeshan Ahmed Ozlem Kalinli 31 9 0 12 Sep 2023
Synthetic Text Generation using Hypergraph Representations Natraj Raman Sameena Shah 10 1 0 06 Sep 2023
Enhancing Small Medical Learners with Privacy-preserving Contextual Prompting Xinlu Zhang Shiyang Li Xianjun Yang Chenxin Tian Yao Qin Linda R. Petzold 24 9 0 22 May 2023
CryptoTL: Private, Efficient and Secure Transfer Learning Roman Walch Samuel Sousa Lukas Helminger Stefanie N. Lindstaedt Christian Rechberger A. Trugler 38 8 0 24 May 2022
Convolutional Neural Networks for Sentence Classification Yoon Kim AILaw VLM 255 13,368 0 25 Aug 2014