Reasoning models with human feedback

From next-token predictor to assistant: supervised fine-tuning teaches the format, then reinforcement learning from human feedback (RLHF) — a reward model trained on human preferences steering PPO — teaches judgment. And the modern turn: RL against verifiable rewards (math checks, unit tests) is what produced the o1/R1 class of reasoning models.