XOR Meta-Residuals Improve Deep Spiking Neural Network Learning

A recent study suggests the use of XOR meta-residuals to improve deep spiking neural networks (SNNs). To tackle the issues of spike redundancy in identity mappings and information loss in non-identity mappings, researchers have developed an OR-ADD (OA) shortcut connection that combines output spikes or currents from two branches. To minimize redundant learning in the backbone branch, Exclusive-OR (XOR) operations are utilized to choose pre-learning residuals. This method, outlined in arXiv:2605.30362, seeks to enhance the learning efficiency and representation ability of SNNs, building on the achievements of ResNet in deep learning. The strategy addresses the challenges posed by current residual structures in deep SNNs, providing an innovative solution for spike redundancy and information loss.