AI RESEARCH
Closing the Theory-Practice Gap in Spiking Transformers via Effective Dimension
arXiv CS.AI
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ArXi:2604.15769v1 Announce Type: cross Spiking transformers achieve competitive accuracy with conventional transformers while offering $38$-$57\times$ energy efficiency on neuromorphic hardware, yet no theoretical framework guides their design. This paper establishes the first comprehensive expressivity theory for spiking self-attention.