Math Word Problem Solving

59 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.

Libraries

Use these libraries to find Math Word Problem Solving models and implementations

Most implemented papers

LLaMA: Open and Efficient Foundation Language Models

facebookresearch/llama arXiv 2023

We introduce LLaMA, a collection of foundation language models ranging from 7B to 65B parameters.

Llama 2: Open Foundation and Fine-Tuned Chat Models

facebookresearch/llama 18 Jul 2023

In this work, we develop and release Llama 2, a collection of pretrained and fine-tuned large language models (LLMs) ranging in scale from 7 billion to 70 billion parameters.

Analysing Mathematical Reasoning Abilities of Neural Models

deepmind/mathematics_dataset ICLR 2019

The structured nature of the mathematics domain, covering arithmetic, algebra, probability and calculus, enables the construction of training and test splits designed to clearly illuminate the capabilities and failure-modes of different architectures, as well as evaluate their ability to compose and relate knowledge and learned processes.

Mistral 7B

mistralai/mistral-src 10 Oct 2023

We introduce Mistral 7B v0. 1, a 7-billion-parameter language model engineered for superior performance and efficiency.

Measuring Mathematical Problem Solving With the MATH Dataset

hendrycks/math 5 Mar 2021

To facilitate future research and increase accuracy on MATH, we also contribute a large auxiliary pretraining dataset which helps teach models the fundamentals of mathematics.

Are NLP Models really able to Solve Simple Math Word Problems?

arkilpatel/SVAMP NAACL 2021

Since existing solvers achieve high performance on the benchmark datasets for elementary level MWPs containing one-unknown arithmetic word problems, such problems are often considered "solved" with the bulk of research attention moving to more complex MWPs.

Let's Verify Step by Step

openai/prm800k Preprint 2023

We conduct our own investigation, finding that process supervision significantly outperforms outcome supervision for training models to solve problems from the challenging MATH dataset.

Mixtral of Experts

hit-scir/chinese-mixtral-8x7b 8 Jan 2024

In particular, Mixtral vastly outperforms Llama 2 70B on mathematics, code generation, and multilingual benchmarks.

LogicSolver: Towards Interpretable Math Word Problem Solving with Logical Prompt-enhanced Learning

yangzhch6/intermwp 17 May 2022

To address this issue and make a step towards interpretable MWP solving, we first construct a high-quality MWP dataset named InterMWP which consists of 11, 495 MWPs and annotates interpretable logical formulas based on algebraic knowledge as the grounded linguistic logic of each solution equation.

Large Language Models are Zero-Shot Reasoners

kojima-takeshi188/zero_shot_cot 24 May 2022

Pretrained large language models (LLMs) are widely used in many sub-fields of natural language processing (NLP) and generally known as excellent few-shot learners with task-specific exemplars.