Plug-and-Play Spiking Operators: Breaking the Nonlinearity Bottleneck in Spiking Transformers

In three linesPlug-and-play framework to convert Transformer nonlinear operators into spiking neural network (SNN) compatible operations. Decomposes Softmax, SiLU, and normalization into primitives (division, exponentiation, L2 norms) executable by LIF neuron groups without fine-tuning. <1% accuracy drop on LLM benchmarks.

Summary generated by Claude — human-verified