sae-jcr-prevents-feature-splitting

Summary

Jump Consistency Regularization is a training penalty that stops the model from redundantly encoding the same concept across multiple nearby features. This keeps the learned representations clean and interpretable, so each feature actually corresponds to one distinct idea rather than a diluted copy of a neighbor's idea.