Arithmetic Addition Classification

This repository contains the code (in PyTorch) for "Arithmetic addition by deep image classification networks: experiments to quantify autonomous reasoning ability" paper by Shuaicheng Liu, Zehao Zhang, Kai Song, and Bing Zeng.

Introduction

In this work, we design a series of experiments, inspired by children’s learning of arithmetic additions of two integers, to showcase that such networks can go beyond the structural features to learn deeper knowledge.

Requirements

• Python3.6+
• PyTorch(1.2.0+)
• torchvision 0.2.0+
• numpy

Train & Evaluation

1. Use the following command to generate the formula images first.

python makeimg.py

2. Run the following code to train se_resnet and observe the classification results directly.

python train.py

3. Results above corresponds to the first experiments validating commutative law by default, you can modify train_val_txt.py to conduct other experiments.

Citation

If you use our code or method in your work, please cite the following:

@misc{liu2019arithmetic,
    title={Arithmetic addition of two integers by deep image classification networks: experiments to quantify their autonomous reasoning ability},
    author={Shuaicheng Liu and Zehao Zhang and Kai Song and Bing Zeng},
    year={2019},
    eprint={1912.04518},
    archivePrefix={arXiv},
    primaryClass={cs.CV}
}