Mathematical reasoning is a fundamental aspect of human intelligence and is applicable in
various fields, including science, engineering, finance, and everyday life. The development …

The field of graph neural networks (GNNs) has seen rapid and incredible strides over the
recent years. Graph neural networks, also known as deep learning on graphs, graph …

Deep learning has become the dominant approach in addressing various tasks in Natural
Language Processing (NLP). Although text inputs are typically represented as a sequence …

We demonstrate that a neural network pretrained on text and fine-tuned on code solves
mathematics course problems, explains solutions, and generates questions at a human …

Solving math word problems requires deductive reasoning over the quantities in the text.
Various recent research efforts mostly relied on sequence-to-sequence or sequence-to-tree …

Automating discovery in mathematics and science will require sophisticated methods of
information extraction and abstract reasoning, including models that can convincingly …

Abstract While Math Word Problem (MWP) solving has emerged as a popular field of study
and made great progress in recent years, most existing methods are benchmarked solely on …

The recent algorithms for math word problems (MWP) neglect to use outside knowledge not
present in the problems. Most of them only capture the word-level relationship and ignore to …

Math word problems solving remains a challenging task where potential semantic and
mathematical logic need to be mined from natural language. Although previous researches …

We study the problem of generating arithmetic math word problems (MWPs) given a math
equation that specifies the mathematical computation and a context that specifies the …