Author

Vito Paolo Pastore

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Preprint Sep 2026

Revisiting Diffusion Fine-Tuning for Unsupervised Domain Adaptation

Diffusion-based unsupervised domain adaptation (UDA) improves cross-domain transfer by generating target-specific synthetic data for downstream adaptation. Existing methods are largely designed for single-target adaptation: when a model trained on one labeled source domain must be adapted to multiple unlabeled target d...

Qi Xuan, Yi-Xiang Wei, Daniele Berardini et al. · 0 citations

Conference Open access Aug 2026

CutClean: Neural Network Pruning for Privacy-Preserving Inference

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 representation imbalances that lead to traditional dataset biases. This poses significant privacy risks when deploying models that process sensi...

Leonardo Magliolo, Vito Paolo Pastore, Giuseppe Valenzise et al. · International Conference on... · 0 citations