Graph-to-tree learning for solving math word problems

J Zhang, L Wang, RKW Lee, Y Bin… - Proceedings of the …, 2020 - aclanthology.org
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 …

Generate & rank: A multi-task framework for math word problems

J Shen, Y Yin, L Li, L Shang, X Jiang, M Zhang… - arxiv preprint arxiv …, 2021 - arxiv.org
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 …

Learning to reason deductively: Math word problem solving as complex relation extraction

Z Jie, J Li, W Lu - arxiv preprint arxiv:2203.10316, 2022 - arxiv.org
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 …

The gap of semantic parsing: A survey on automatic math word problem solvers

D Zhang, L Wang, L Zhang, BT Dai… - IEEE transactions on …, 2019 - ieeexplore.ieee.org
Solving mathematical word problems (MWPs) automatically is challenging, primarily due to
the semantic gap between human-readable words and machine-understandable logics …

Modeling intra-relation in math word problems with different functional multi-head attentions

J Li, L Wang, J Zhang, Y Wang, BT Dai, D Zhang - 2019 - ink.library.smu.edu.sg
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 …

Tree-structured decoding for solving math word problems

Q Liu, W Guan, S Li, D Kawahara - Proceedings of the 2019 …, 2019 - aclanthology.org
Automatically solving math word problems is an interesting research topic that needs to
bridge natural language descriptions and formal math equations. Previous studies …