Math Word Problem Solving
62 papers with code • 11 benchmarks • 17 datasets
A math word problem is a mathematical exercise (such as in a textbook, worksheet, or exam) where significant background information on the problem is presented in ordinary language rather than in mathematical notation. As most word problems involve a narrative of some sort, they are sometimes referred to as story problems and may vary in the amount of technical language used.
Benchmarks
These leaderboards are used to track progress in Math Word Problem Solving
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Libraries
Use these libraries to find Math Word Problem Solving models and implementations
MATH
SVAMP
ASDiv
MathQA
IconQA
MathVista
ALG514
Latest papers with no code
Data Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving
Math Word Problem (MWP) solving presents a challenging task in Natural Language Processing (NLP).
An Expression Tree Decoding Strategy for Mathematical Equation Generation
To generate a tree with expression as its node, we employ a layer-wise parallel decoding strategy: we decode multiple independent expressions (leaf nodes) in parallel at each layer and repeat parallel decoding layer by layer to sequentially generate these parent node expressions that depend on others.
Skills-in-Context Prompting: Unlocking Compositionality in Large Language Models
Compositional generalization empowers the LLMs to solve problems that are harder than the ones they have seen (i. e., easy-to-hard generalization), which is a critical reasoning capability of human-like intelligence.
CMATH: Can Your Language Model Pass Chinese Elementary School Math Test?
We present the Chinese Elementary School Math Word Problems (CMATH) dataset, comprising 1. 7k elementary school-level math word problems with detailed annotations, source from actual Chinese workbooks and exams.
Math Word Problem Solving by Generating Linguistic Variants of Problem Statements
In order to ameliorate this issue, in this paper, we propose a framework for MWP solvers based on the generation of linguistic variants of the problem text.
Let GPT be a Math Tutor: Teaching Math Word Problem Solvers with Customized Exercise Generation
In this paper, we present a novel approach for distilling math word problem solving capabilities from large language models (LLMs) into smaller, more efficient student models.
MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving
Math word problem (MWP) solving faces a dilemma in number representation learning.
Towards Interpretable Math Word Problem Solving with Grounded Linguistic Logic Reasoning
Automatically math word problem (MWP) solving is a challenging artificial intelligence task since a machine should be able to not only understand problem comprehensively on linguistics but also the grounded math logic entailed in problem.
Generate & Rank: A Multi-task Framework for Math Word Problems
Math word problem (MWP) is a challenging and critical task in natural language processing.
Generating Equation by Utilizing Operators : GEO model
In this paper, we propose the GEO (Generation of Equations by utilizing Operators) model that does not use hand-crafted features and addresses two issues that are present in existing neural models: 1. missing domain-specific knowledge features and 2. losing encoder-level knowledge.
