Evaluating the Prompt Steerability of Large Language Models
Erik Miehling, Michael Desmond, Karthikeyan Natesan Ramamurthy, Elizabeth M. Daly, Kush R. Varshney, Eitan Farchi, Pierre Dognin, Jesus Rios
Abstract
Building pluralistic AI requires designing models that are able to be shaped to represent a wide range of value systems and cultures. Achieving this requires first being able to evaluate the degree to which a given model is capable of reflecting various personas. To this end, we propose a benchmark for evaluating the steerability of model personas as a function of prompting. Our design is based on a formal definition of prompt steerability, which analyzes the degree to which a model’s joint behavioral distribution can be shifted from its baseline. By defining steerability indices and inspecting how these indices change as a function of steering effort, we can estimate the steerability of a model across various persona dimensions and directions. Our benchmark reveals that the steerability of many current models is limited — due to both a skew in their baseline behavior and an asymmetry in their steerability across many persona dimensions. We release an implementation of our benchmark at https://github.com/IBM/prompt-steering.
BibTeX
@inproceedings{miehling-etal-2025-evaluating,
title = "Evaluating the Prompt Steerability of Large Language Models",
author = "Miehling, Erik and
Desmond, Michael and
Natesan Ramamurthy, Karthikeyan and
Daly, Elizabeth M. and
Varshney, Kush R. and
Farchi, Eitan and
Dognin, Pierre and
Rios, Jesus and
Bouneffouf, Djallel and
Liu, Miao and
Sattigeri, Prasanna",
editor = "Chiruzzo, Luis and
Ritter, Alan and
Wang, Lu",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)",
month = apr,
year = "2025",
address = "Albuquerque, New Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-long.400/",
pages = "7874--7900",
ISBN = "979-8-89176-189-6"
}