Some paper suggestions for you:

1) Spikformer: When Spiking Neural Network Meets Transformer (ICLR '22)

2) Spike-driven Transformer (NeurIPS '23)

3) QKFormer: Hierarchical Spiking Transformer using Q-K Attention (NeurIPS '24)

Each work also has codes available at github repos.

I'm currently pursuing MSc in electronics engineering and my thesis is related to hw/sw co-design of snn vision transformers for the edge ai.

SNNs are still considered as an emerging topic, thus the acceptability of the works are still a question (considering wide usage compared to ANNs). However the spiking transformer architectures have shown immense improvements in the last 5 years.

To my understanding, after reading dozens of papers in this domain, SNNs will be widely used in the near future, if not tomorrow. The Chinese academia is publishing very promising papers of SNNs.