MLn CLUB · WEEK 3
Tiny Recursive Models
About this week
This paper introduces Tiny Recursive Models (TRM), which drastically simplifies previous hierarchical reasoning approaches while achieving better performance on puzzle tasks like Sudoku and ARC-AGI. Using just a single 2-layer network with 7M parameters, TRM outperforms much larger language models by recursively refining both its current answer and internal reasoning state. The work challenges conventional scaling wisdom by showing that smaller networks with deeper recursion can outperform larger models, offering a parameter-efficient approach to complex reasoning tasks. Discussion at 20:00, (optional) quiet reading from 19:00.