Code for Graph-to-Tree Learning for Solving Math Word Problems (ACL 2020)

Overview

Graph-to-Tree Learning for Solving Math Word Problems

PyTorch implementation of Graph based Math Word Problem solver described in our ACL 2020 paper Graph-to-Tree Learning for Solving Math Word Problems. In this work, we propose a solution for Math Word Problem Solving via graph neural network.

Steps to run the experiments

Requirements

  • Python 3.6
  • >= PyTorch 1.0.0

For more details, please refer to requiremnt file.

Training

[MATH23K]

first get into the math23k directory:

  • cd math23k

training-test setting :

  • python run_seq2tree_graph.py

cross-validation setting :

  • python cross_valid_graph2tree.py

[MAWPS]

cross-validation setting :

  • cd mawps
  • python cross_valid_mawps.py

Contact

  • As I have graduated from my master school, my school email address will be invalid soon. If you have further questions about our work, you can refer to my new email address [email protected].

Reference

@article{zhang2020graph2tree,
  title={Graph-to-Tree Learning for Solving Math Word Problems},
  author={Zhang, Jipeng and Wang, Lei and Lee, Roy Ka-Wei and Bin, Yi and Shao, Jie and Lim, Ee-Peng},
  journal={ACL 2020},
  year={2020}
}
Owner
Jipeng Zhang
Jipeng Zhang
Segmentation for medical image.

EfficientSegmentation Introduction EfficientSegmentation is an open source, PyTorch-based segmentation framework for 3D medical image. Features A whol

68 Nov 28, 2022
GPT-Code-Clippy (GPT-CC) is an open source version of GitHub Copilot

GPT-Code-Clippy (GPT-CC) is an open source version of GitHub Copilot, a language model -- based on GPT-3, called GPT-Codex -- that is fine-tuned on publicly available code from GitHub.

2.3k Jan 09, 2023
The implementation code for "DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruction"

DAGAN This is the official implementation code for DAGAN: Deep De-Aliasing Generative Adversarial Networks for Fast Compressed Sensing MRI Reconstruct

TensorLayer Community 159 Nov 22, 2022
The implementation for paper Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets.

Joint t-sne This is the implementation for paper Joint t-SNE for Comparable Projections of Multiple High-Dimensional Datasets. abstract: We present Jo

IDEAS Lab 7 Dec 18, 2022
A Context-aware Visual Attention-based training pipeline for Object Detection from a Webpage screenshot!

CoVA: Context-aware Visual Attention for Webpage Information Extraction Abstract Webpage information extraction (WIE) is an important step to create k

Keval Morabia 41 Jan 01, 2023
A supplementary code for Editable Neural Networks, an ICLR 2020 submission.

Editable neural networks A supplementary code for Editable Neural Networks, an ICLR 2020 submission by Anton Sinitsin, Vsevolod Plokhotnyuk, Dmitry Py

Anton Sinitsin 32 Nov 29, 2022
Code for "Long-tailed Distribution Adaptation"

Long-tailed Distribution Adaptation (Accepted in ACM MM2021) This project is built upon BBN. Installation pip install -r requirements.txt Usage Traini

Zhiliang Peng 10 May 18, 2022
Official implementation of the paper 'Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution'

DASR Paper Efficient and Degradation-Adaptive Network for Real-World Image Super-Resolution Jie Liang, Hui Zeng, and Lei Zhang. In arxiv preprint. Abs

81 Dec 28, 2022
Geometry-Free View Synthesis: Transformers and no 3D Priors

Geometry-Free View Synthesis: Transformers and no 3D Priors Geometry-Free View Synthesis: Transformers and no 3D Priors Robin Rombach*, Patrick Esser*

CompVis Heidelberg 293 Dec 22, 2022
MicroNet: Improving Image Recognition with Extremely Low FLOPs (ICCV 2021)

MicroNet: Improving Image Recognition with Extremely Low FLOPs (ICCV 2021) A pytorch implementation of MicroNet. If you use this code in your research

Yunsheng Li 293 Dec 28, 2022
This project generates news headlines using a Long Short-Term Memory (LSTM) neural network.

News Headlines Generator bunnysaini/Generate-Headlines Goal This project aims to generate news headlines using a Long Short-Term Memory (LSTM) neural

Bunny Saini 1 Jan 24, 2022
a reimplementation of Optical Flow Estimation using a Spatial Pyramid Network in PyTorch

pytorch-spynet This is a personal reimplementation of SPyNet [1] using PyTorch. Should you be making use of this work, please cite the paper according

Simon Niklaus 269 Jan 02, 2023
Code for the paper Task Agnostic Morphology Evolution.

Task-Agnostic Morphology Optimization This repository contains code for the paper Task-Agnostic Morphology Evolution by Donald (Joey) Hejna, Pieter Ab

Joey Hejna 18 Aug 04, 2022
Fuwa-http - The http client implementation for the fuwa eco-system

Fuwa HTTP The HTTP client implementation for the fuwa eco-system Example import

Fuwa 2 Feb 16, 2022
A distributed deep learning framework that supports flexible parallelization strategies.

FlexFlow FlexFlow is a deep learning framework that accelerates distributed DNN training by automatically searching for efficient parallelization stra

528 Dec 25, 2022
Advanced yabai wooting scripts

Yabai Wooting scripts Installation requirements Both https://github.com/xiamaz/python-yabai-client and https://github.com/xiamaz/python-wooting-rgb ne

Max Zhao 3 Dec 31, 2021
Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators..

ARAPReg Code for ICCV 2021 paper: ARAPReg: An As-Rigid-As Possible Regularization Loss for Learning Deformable Shape Generators.. Installation The cod

Bo Sun 132 Nov 28, 2022
ThunderSVM: A Fast SVM Library on GPUs and CPUs

What's new We have recently released ThunderGBM, a fast GBDT and Random Forest library on GPUs. add scikit-learn interface, see here Overview The miss

Xtra Computing Group 1.4k Dec 22, 2022
FSL-Mate: A collection of resources for few-shot learning (FSL).

FSL-Mate is a collection of resources for few-shot learning (FSL). In particular, FSL-Mate currently contains FewShotPapers: a paper list which tracks

Yaqing Wang 1.5k Jan 08, 2023
This is a deep learning-based method to segment deep brain structures and a brain mask from T1 weighted MRI.

DBSegment This tool generates 30 deep brain structures segmentation, as well as a brain mask from T1-Weighted MRI. The whole procedure should take ~1

Luxembourg Neuroimaging (Platform OpNeuroImg) 2 Oct 25, 2022