Justify Your Prompts!

Authors

Keywords:

Metascience, Evaluation, Prompt Engineering, Natural Language Generation (NLG), Large Language Models (LLMs)

Abstract

When you use a large language model (LLM) in your research, you often need to formulate a prompt to elicit some relevant output from the LLM. This step is challenging since (1) LLMs are known to be brittle and their results may vary drastically between different prompts; and (2) for any given task, there are infinitely many possible prompts. Thus we end up with the following problem: if you cannot try out infinitely many prompts, how do you justify your selected prompt? This paper discusses different ways in which authors may motivate their choices, and urges authors to consider how their prompting strategy might be justified.

Author Biography

  • Emiel van Miltenburg, Tilburg University

    Emiel van Miltenburg is an assistant professor at Tilburg University, working on Natural Language Generation. His research mainly focuses on automatic image description, evaluation, and accessibility. Emiel has served on the SIGGEN board from 2021 to 2024.

Published

2026-10-15