3 papers
cs.NE2026
Privacy-Preserving Distributed Optimization Under Time Constraints Using Secure Multi-Party Computation and Evolutionary Algorithms
Sebastian Gruber, Tobias Harzfeld, Christoph G. Schuetz +2
In distributed optimization, multiple parties collaborate to find an optimal solution to a problem. Privacy-preserving distributed optimization uses techniques, such as secure mult…
cs.CY2025
Exploring the Use of Predictive Analytics by Austrian Tax Authorities: A Qualitative Study within the Task-Technology Fit Model
Simon Staudinger, Christoph G. Schuetz, Marina Luketina
Taxes finance important government services that are now taken for granted in our society, such as infrastructure, health care, or retirement pensions. Tax authorities everywhere s…
cs.CL2025
Using Large Language Models for Legal Decision-Making in Austrian Value-Added Tax Law: A Comparative Study
Marina Luketina, Andrea Benkel, Christoph G. Schuetz
This paper provides an experimental evaluation of the capability of large language models (LLMs) to assist in legal decision-making within the framework of Austrian and European Un…