Tiny 155K‑parameter transformer learns a causal world map from pure move data
A 155K‑parameter transformer, trained only on move symbols, spontaneously builds an internal spatial map of its grid world. A linear probe can read and even edit that map, instantly altering the model's behavior—showing world‑modeling emergent even in tiny nets.