Guiding Text-to-Text Privatization by Syntax

2 June 2023

Papers citing "Guiding Text-to-Text Privatization by Syntax"

9 / 9 papers shown

Title
Data-adaptive Differentially Private Prompt Synthesis for In-Context Learning Fengyu Gao Ruida Zhou T. Wang Cong Shen Jing Yang 41 2 0 15 Oct 2024
Disentangling the Linguistic Competence of Privacy-Preserving BERT Stefan Arnold Nils Kemmerzell Annika Schreiner 35 0 0 17 Oct 2023
Privacy-Preserving Prompt Tuning for Large Language Model Services Yansong Li Zhixing Tan Yang Liu SILM VLM 53 64 0 10 May 2023
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 35 18 0 22 Jan 2023
TEM: High Utility Metric Differential Privacy on Text Ricardo Silva Carvalho Theodore Vasiloudis Oluwaseyi Feyisetan 39 37 0 16 Jul 2021
On a Utilitarian Approach to Privacy Preserving Text Generation Zekun Xu Abhinav Aggarwal Oluwaseyi Feyisetan Nathanael Teissier 37 24 0 23 Apr 2021
Extracting Training Data from Large Language Models Nicholas Carlini Florian Tramèr Eric Wallace Matthew Jagielski Ariel Herbert-Voss ... Tom B. Brown D. Song Ulfar Erlingsson Alina Oprea Colin Raffel MLAU SILM 290 1,831 0 14 Dec 2020
GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding Alex Jinpeng Wang Amanpreet Singh Julian Michael Felix Hill Omer Levy Samuel R. Bowman ELM 299 6,996 0 20 Apr 2018
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 305 31,280 0 16 Jan 2013