Numerical Correlation in Text
Daniel Spokoyny, Chien-Sheng Wu, Caiming Xiong · 2022
Evaluation of quantitative reasoning of large language models is an important step towards understanding their current capabilities and limitations.We propose a new task, Numerical Correlation in Text, which requires models to identify the correlation between two numbers in a sentence.To this end, we introduce a new dataset, which contains over 2,000 Wikipedia sentences with two numbers and their correlation labels.Using this dataset we are able to show that recent numerically aware pretraining methods for language models do not help generalization on this task posing a challenge for future work in this area.1