Spike-Driven Neighborhood Attention for Vision Transformers
Spiking Neural Networks (SNNs) promise ultra-low-power, event-driven computation; however, current efforts to integrate self-attention into spiking transformers predominantly rely on global attention mechanisms, introducing growing token complexity when scaling and diluting discriminative feature representations. We in...