Justify Your Prompts!

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.

Authors

Institutions

Publication Details

Journal
Computational Linguistics
Published
2026-04-15
DOI
https://doi.org/10.1162/coli.a.620
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Justify Your Prompts!

Eduardo Calò, Patrícia Schmidtová, David M. Howcroft, Simon Mille et al.
Computational Linguistics
Artificial Intelligence in Healthcare and Education
article

Justify Your Prompts!

Eduardo Calò, Patrícia Schmidtová, David M. Howcroft, Simon Mille, Emiel van Miltenburg, Saad Mahamood, Leo Leppänen
article en

Abstract

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.

Computational Linguistics
Utrecht University (NL), Tilburg University (NL), University of Aberdeen (GB), Charles University (CZ), Adaptimmune (United Kingdom) (GB), Edgware Community Hospital (GB), University of Jyväskylä (FI)
Openalex Percentile: Top 14%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.