Language models have become very popular recently and many claims have been made about their abilities, including for commonsense reasoning. Given the increasingly better results of current language models on previous static benchmarks for commonsense reasoning, we explore an alternative dialectical evaluation. The goal of this kind of evaluation is not to obtain an aggregate performance value but to find failures and map the boundaries of the system. Dialoguing with the system gives the opportunity to check for consistency and get more reassurance of these boundaries beyond anecdotal evidence. In this paper we conduct some qualitative investigations of this kind of evaluation for the particular case of spatial reasoning (which is a fundamental aspect of commonsense reasoning). We conclude with some suggestions for future work both to improve the capabilities of language models and to systematise this kind of dialectical evaluation.
@article{arxiv.2304.11164,
title = {Dialectical language model evaluation: An initial appraisal of the commonsense spatial reasoning abilities of LLMs},
author = {Anthony G Cohn and Jose Hernandez-Orallo},
journal= {arXiv preprint arXiv:2304.11164},
year = {2023}
}