Improve mathematical reasoning with process supervision

We trained a model to achieve a new state of the art in mathematical problem solving by rewarding each correct step of reasoning (“process supervision”) instead of just rewarding the final correct answer (“result supervision”) ). In addition to improving performance over output monitoring, process monitoring also has an important alignment benefit: it directly trains the model to produce a human-approved chain of thought.