AI RESEARCH
Elastic Spiking Transformers for Efficient Gesture Understanding
arXiv CS.CV
•
ArXi:2605.13869v1 Announce Type: cross Spiking Neural Networks (SNNs), particularly Spiking Transformers, offer energy-efficient processing of event-based sensor data for healthcare applications. Yet current architectures are rigid: they are trained and deployed as static networks with fixed parameter counts and computational graphs. This limits deployment on neuromorphic hardware such as Loihi and SpiNNaker, where on-chip constraints often require smaller models that trade accuracy for feasibility. We.