test-time-scaling-reflective

Scale model performance at test time by generating multiple reasoning trajectories and selecting the best using a self-supervised process reward model. MetaStone-S1 achieves 32B-equivalent performance using only 32B parameters and 53M for trajectory scoring, learning process rewards from outcome labels alone without process annotations.

Independent GitHub snapshot · Automated classification · Original documentation governs