Small Recursive Reasoning Models
Deep Learning
Reasoning
A survey of small networks that reason by test-time recursion
A distinct line of reasoning models uses small neural networks that are recursively unrolled at test time. These models seek to trade parameter count for iterative computation and have been studied on structured tasks such as Sudoku and ARC-AGI.
This book examines recursive reasoning models through their technical foundations, prior art, empirical evaluation, and critiques. It also connects them to latent reasoning, test-time scaling, implementation choices, and open problems.