# Monosemantic Feature **Entity class:** Concept or analytic term **Domain:** Machine Learning / Interpretability **Doc Type:** Technical Concept Node **Maturity:** Active Research Concept **Related:** [[Sparse Autoencoder]], [[Superposition]], [[Latent Space]] --- ## Definition A **monosemantic feature** is an internal model feature that responds predominantly to one interpretable concept or coherent family of conditions rather than mixing many unrelated meanings. Sparse-autoencoder research attempts to recover approximately monosemantic directions from superposed activation spaces. ## Continuity relevance Interpretable feature directions help explain semantic traversability in artificial systems, but they do not supply lived provenance or demonstrate an enduring first-person self. ## Neurotech cluster route **Collection:** [[collections/Neurotech|Neurotech]] **Source articles:** [[articles/The Architecture of Continuity and Emerging Neuroinformatics Standards|The Architecture of Continuity and Emerging Neuroinformatics Standards]] ## Relationships [[wiki/Monosemantic Feature|Monosemantic Feature]] is related to [[collections/Neurotech|Neurotech]] through [[articles/The Architecture of Continuity and Emerging Neuroinformatics Standards|The Architecture of Continuity and Emerging Neuroinformatics Standards]]. <!-- BEGIN HUMANIZED RELATIONSHIPS 2026-09-11 --> This entry's documented connections are expressed in its definition and related-work routes, with provenance retained in the source-linked material. <!-- END HUMANIZED RELATIONSHIPS 2026-09-11 --> ## Related Work in the Corpus <!-- BEGIN HUMANIZED CORPUS ROUTES 2026-09-11 --> - In [[articles/The Architecture of Continuity and Emerging Neuroinformatics Standards|The Architecture of Continuity and Emerging Neuroinformatics Standards]], **The Architecture of Continuity and Emerging Neuroinformatics Standards** provides the narrative context for **Monosemantic Feature**: Representation and reconstructive memory: distributed relational compression · latent space · superposition · sparse autoencoders · monosemantic features · dictionary learning · variational autoencoders · hippocampal replay ·… <!-- END HUMANIZED CORPUS ROUTES 2026-09-11 -->