C$^{2}$R: Cross-sample Consistency Regularization Mitigates Feature Splitting and Absorption in Sparse Autoencoders
C²R regularization eliminates feature splitting and absorption in large Sparse Autoencoders via cross-sample consistency constraints for improved LLM interpretability.