Recent research has demonstrated that prompting language models to generate reasoning steps can improve performance on various natural language reasoning tasks. But how to supervise such models? Is it better to employ outcome-based approaches that supervise the final answer, or process-based approaches that supervise the reasoning process itself? In the new paper Solving Math Word Problems With Process- and Outcome-based Feedback, a DeepMind research team