1 citations · 2 across the 4 of their papers we have counts for
4 papers
Routing in Sparsely-gated Language Models responds to Context
Stefan Arnold, Marian Fietta, Dilara Yesilbas
Language Models (LMs) recently incorporate mixture-of-experts layers consisting of a router and a collection of experts to scale up their parameter count given a fixed computationa…
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…
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…
Demystifying the Effects of Non-Independence in Federated Learning
Stefan Arnold, Dilara Yesilbas
Federated Learning (FL) enables statistical models to be built on user-generated data without compromising data security and user privacy. For this reason, FL is well suited for on…