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papersSEP 11 04:00 UTC

Study Proposes Neuron Specialization as Distinct Form of Feature Learning in MLPs

A revised arXiv paper argues that feature learning in neural networks is not fully captured by the prevailing view that networks converge on a single global low-dimensional representation. The authors point to neuron specialization inside multilayer perceptrons as an additional, separate mechanism through which features are acquired and organized. The work aims to broaden the theoretical picture of how networks structure what they learn.

arXiv feature learning multilayer perceptrons neural network interpretability neuron specialization representation learning

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arXiv cs.LGRevenge of Monosemanticity: Neuron Specialization as a New Form of Feature Learning in MLPs ↗SEP 11 04:00 UTC