Abstract: Existing quantization approaches often suffer from significant accuracy degradation when compressing hybrid convolution and transformer models with low bit-width. This paper presents ...
Abstract: Brain-inspired Spiking Neural Networks (SNNs) have attracted significant attention for their potential to enable energy-efficient computing on neuromorphic hardware. However, the current SNN ...
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