Semantic-based Data Augmentation for Math Word Problems. (arXiv:2201.02489v1 [cs.CL])

It's hard for neural MWP solvers to deal with tiny local variances. In MWP
task, some local changes conserve the original semantic while the others may
totally change the underlying logic. Currently, existing datasets for MWP task
contain limited samples which are key for neural models to learn to
disambiguate different kinds of local variances in questions and solve the
questions correctly. In this paper, we propose a set of novel data augmentation
approaches to supplement existing datasets with such …

arxiv augmentation data math semantic