Stanford U & Open AI’s Meta-Prompting Elevates Language Model Performance, Surpassing Standard Prompting by 17%

In a new paper Meta-Prompting: Enhancing Language Models with Task-Agnostic Scaffolding, the team introduces meta-prompting. This innovative scaffolding approach proves to be highly effective, surpassing standard prompting by 17.1%, expert (dynamic) prompting by 17.3%, and multi-persona prompting by 15.2%.

ai artificial intelligence deep-neural-networks dynamic expert language language model language models machine learning machine learning & data science meta meta-learning ml open ai paper performance prompting research standard stanford team technology