This paper presents a novel framework for evaluating Neural Language Models' linguistic abilities using a constructionist approach. Not only is the usage-based model in line with the underlying stochastic philosophy of neural architectures, but it also allows the linguist to keep meaning as a determinant factor in the analysis. We outline the framework and present two possible scenarios for its application.
@article{arxiv.2302.03589,
title = {CALaMo: a Constructionist Assessment of Language Models},
author = {Ludovica Pannitto and Aurélie Herbelot},
journal= {arXiv preprint arXiv:2302.03589},
year = {2024}
}