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Open access Jul 2026

Test Case Prioritization for DNNs via Neural Collapse Instability

A Neural-Collapse-Inspired Prioritization (NCIP) framework that replaces absolute confidence with cross-checkpoint prediction variability in the terminal training regime, where model geometry becomes highly structured and achieves strong performance in early fault discovery compared with competitive baselines.

Chun-Yu Liu, Ming-Yuan Li, Yang Li et al. · 0 citations
Open access Jul 2026

Federated heterogeneous subgraph learning with meta-path-guided role mapping and condensation

A new federated learning framework, federated heterogeneous subgraph learning with meta-path-guided role mapping and condensation (FedPRC) with a meta-path-guided virtual node generation method, which significantly outperforms existing federated graph learning baseline models in node classification tasks.

Yanjin Cheng, Wen-Min Li, Su-Lu Qin et al. · 0 citations

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