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Napping-inspired offline mechanism proposed for recurrent spiking neural networks
A new arXiv preprint examines how biological systems use offline periods, such as sleep or rest, to keep their internal models both accurate and simple. The authors adapt this idea into a "napping" paradigm for recurrent spiking neural networks, aiming to balance predictive accuracy against generalization. The work is a research contribution and reports no released model or product.