Toy Models of Superposition

Editorial record

Plain-language summary

Using small toy models, the authors demonstrate that when features are sparse a network represents many of them as overlapping directions rather than one-per-neuron, trading interference for capacity. They map when superposition appears and how it organizes into geometric structures. This reframed why interpretability is hard and motivated methods to pull features apart.