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Distributed neural network weights can now be cryptographically audited for multi-party collusion using zero-knowledge proofs, achieving certified sub-0.1% false-accusation rates across hundreds of leaked model mixtures.
CPDA aligns class-conditional latent paths, outperforming 30 existing methods in unsupervised time-series domain adaptation.
Combining advanced model compression with hardware-aware architecture search can drastically enhance real-time GNSS interference monitoring on low-resource devices.