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Graph-to-tree learning for solving math word problems
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 …
generating solution expression for the math word problem (MWP), most of these models do …
Generate & rank: A multi-task framework for math word problems
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 …
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
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 …
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
Solving mathematical word problems (MWPs) automatically is challenging, primarily due to
the semantic gap between human-readable words and machine-understandable logics …
the semantic gap between human-readable words and machine-understandable logics …
Modeling intra-relation in math word problems with different functional multi-head attentions
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. Although these models have the ability to capture features without manual …
Tree-structured decoding for solving math word problems
Automatically solving math word problems is an interesting research topic that needs to
bridge natural language descriptions and formal math equations. Previous studies …
bridge natural language descriptions and formal math equations. Previous studies …