Principled Instructions Are All You Need for Questioning LLaMA-1/2, GPT-3.5/4

TL;DR

This paper presents 26 guiding principles to improve question formulation and prompting strategies for large language models, aiming to enhance understanding and performance across different model scales.

Contribution

The paper introduces a set of 26 principles that systematically improve prompting techniques for large language models, validated through extensive experiments on multiple models.

Findings

Guiding principles improve prompt effectiveness across models

Enhanced understanding of model behaviors with principled prompting

Consistent performance gains demonstrated on LLaMA and GPT models

Abstract

This paper introduces 26 guiding principles designed to streamline the process of querying and prompting large language models. Our goal is to simplify the underlying concepts of formulating questions for various scales of large language models, examining their abilities, and enhancing user comprehension on the behaviors of different scales of large language models when feeding into different prompts. Extensive experiments are conducted on LLaMA-1/2 (7B, 13B and 70B), GPT-3.5/4 to verify the effectiveness of the proposed principles on instructions and prompts design. We hope that this work can provide a better guide for researchers working on the prompting of large language models. Project page is available at https://github.com/VILA-Lab/ATLAS.