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

While the recent tree-based neural models have demonstrated promising results in
generating solution expression for the math word problem (MWP), most of these models do …

Math word problem (MWP) is a challenging and critical task in natural language processing.
Many recent studies formalize MWP as a generation task and have adopted sequence-to …

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 …

Geometry problem solving has attracted much attention in the NLP community recently. The
task is challenging as it requires abstract problem understanding and symbolic reasoning …

Researchers have been interested in developing AI tools to help students learn various
mathematical subjects. One challenging set of tasks for school students is learning to solve …

Solving mathematical word problems (MWPs) automatically is challenging, primarily due to
the semantic gap between human-readable words and machine-understandable logics …

Several deep learning models have been proposed for solving math word problems (MWPs)
automatically. Although these models have the ability to capture features without manual …

Automatically solving math word problems is an interesting research topic that needs to
bridge natural language descriptions and formal math equations. Previous studies …

With the advancements in natural language processing tasks, math word problem solving
has received increasing attention. Previous methods have achieved promising results but …