Seong-Eun Kim

Rethinking Attention in Spiking Transformers: Overcoming Density Bias with Set Similarity

Recent Spiking Transformer models have explored a variety of attention mechanisms beyond standard dot-product formulations. However, many existing similarity-based spiking attention formulations remain inherently sensitive to firing density, causing neurons with high spike rates to dominate attentio…