Driving Context into Text-to-Text Privatization

2 June 2023

Papers citing "Driving Context into Text-to-Text Privatization"

8 / 8 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
Differentially Private Natural Language Models: Recent Advances and Future Directions Lijie Hu Ivan Habernal Lei Shen Di Wang AAML 32 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 1,824 0 14 Dec 2020
Knowledge Enhanced Contextual Word Representations Matthew E. Peters Mark Neumann IV RobertL.Logan Roy Schwartz Vidur Joshi Sameer Singh Noah A. Smith 234 656 0 09 Sep 2019
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 6,984 0 20 Apr 2018
Efficient Estimation of Word Representations in Vector Space Tomáš Mikolov Kai Chen G. Corrado J. Dean 3DV 296 31,267 0 16 Jan 2013