Learning to Rank Architectures: A Small Model That Guides Neural Architecture Search
A tiny recursive reasoning model trained to rank architectures by predicted performance achieves 8-10x sample efficiency over random search and transfers zero-shot across datasets with minimal loss in ranking quality.