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Since methodologically there are no one-size-fits-all neurons, given the same structure, task-based neurons can enhance","title":"No One-Size-Fits-All Neurons: Task-based Neurons for Artificial Neural Networks","url":"https://arxiv.org/abs/2405.02369","vendor":"arxiv_cs_ai"},"summary":"arXiv:2405.02369v2 Announce Type: replace-cross \nAbstract: In the past decade, many successful networks are on novel architectures, which almost exclusively use the same type of neurons. Recently, more and more deep learning studies have been inspired by the idea of NeuroAI and the neuronal diversity observed in human brains, leading to the proposal of novel artificial neuron designs. Designing well-performing neurons represents a new dimension relative to designing well-performing neural architectures. Biologically, the brain does not rely on a single type of neuron that universally functions in all aspects. Instead, in our brain, neurons are often task-based. 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