Toward Uncertainty-Aware and Generalizable Neural Decoding for Quantum LDPC Codes
This work develops a multi-phase training framework with enhanced cross-domain robustness enabling decoding beyond the training set called Sequential Aggregate Generalization under Uncertainty, and demonstrates that both QuBA and SAGU consistently outperform the classical baseline belief propagation.