3 papers
cs.CL2023
Disentangling the Linguistic Competence of Privacy-Preserving BERT
Stefan Arnold, Nils Kemmerzell, Annika Schreiner
Differential Privacy (DP) has been tailored to address the unique challenges of text-to-text privatization. However, text-to-text privatization is known for degrading the performan…
cs.CL2023
Guiding Text-to-Text Privatization by Syntax
Stefan Arnold, Dilara Yesilbas, Sven Weinzierl
Metric Differential Privacy is a generalization of differential privacy tailored to address the unique challenges of text-to-text privatization. By adding noise to the representati…
cs.CL2023
Driving Context into Text-to-Text Privatization
Stefan Arnold, Dilara Yesilbas, Sven Weinzierl
\textit{Metric Differential Privacy} enables text-to-text privatization by adding calibrated noise to the vector of a word derived from an embedding space and projecting this noisy…