“Probabilistic Tiny Recursive Model”
This paper makes Tiny Recursive Models stochastic at test time by adding Gaussian noise, running parallel rollouts, and using the existing Q head to pick the best answer.
With no retraining and no task-specific tricks, its PPBench jumps from 62.6% to 91.2%, while Sudoku-Extreme jumps from 87.4% to 98.75%.