2 papers
cs.LG2026
CutClean: Neural Network Pruning for Privacy-Preserving Inference
Leonardo Magliolo, Vito Paolo Pastore, Giuseppe Valenzise +1
Neural networks are increasingly deployed in high-stakes applications with growing privacy leakage concerns. We show that this privacy leakage can occur even in the absence of repr…
cs.CY2026
Two Means to an End Goal: Connecting Explainability and Contestability in the Regulation of Public Sector AI
Timothée Schmude, Mireia Yurrita, Kars Alfrink +3
Explainability and its emerging counterpart contestability have become important normative and design principles for trustworthy AI as they enable users and subjects to understand…