reasoning-via-sampling

Improves base model reasoning through iterative sampling without training or fine-tuning. Uses MCMC-inspired sampling to extract latent reasoning from pretrained models, achieving RL-comparable gains on math, coding, and QA tasks while preserving diversity.

Independent GitHub snapshot · Automated classification · Original documentation governs