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Sparse autoencoders (SAEs) add a sparsity penalty (such as L1 regularization) to the loss function, forcing only a small number of neurons in the hidden layer to be active at the same time; the hidden layer can be viewed as a set of "latent features," each corresponding to a direction in activation space.
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11/2/2026
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