How Much Consistency Is Your Accuracy Worth?
Abstract
Contrast set consistency is a robustness measurement that evaluates the rate at which a model correctly responds to all instances in a bundle of minimally different examples relying on the same knowledge. To draw additional insights, we propose to complement consistency with relative consistency -- the probability that an equally accurate model would surpass the consistency of the proposed model, given a distribution over possible consistencies. Models with 100% relative consistency have reached a consistency peak for their accuracy. We reflect on prior work that reports consistency in contrast sets and observe that relative consistency can alter the assessment of a model's consistency compared to another. We anticipate that our proposed measurement and insights will influence future studies aiming to promote consistent behavior in models.
Cite
@article{arxiv.2310.13781,
title = {How Much Consistency Is Your Accuracy Worth?},
author = {Jacob K. Johnson and Ana Marasović},
journal= {arXiv preprint arXiv:2310.13781},
year = {2023}
}
Comments
BlackboxNLP 2023 accepted paper camera-ready version; 6 pages main, 3 pages appendix