This repository is the implementation for the AAAI2021 accepted paper:
Yining Hong, Qing Li, Daniel Ciao, Siyuan Huang and Song-Chun Zhu Learning by Fixing: Solving Math Word Problems with Weak Supervision AAAI2021.
A Seq2Tree Neural Network containing top-down Recursive Neural Network and bottom-up Recursive Neural Network
An abductive learning framework that can fix the wrong expressions generated by Seq2Tree
- python 3
- PyTorch 0.4.1
- Math23K:
python run_seq2tree.py --model='ma-fix' --nstep=50 --name='ma-fix'
python run_seq2tree.py --model='fix' --nstep=50 --name='fix'
python run_seq2tree.py --model='reinforce' --name='reinforce'
python run_seq2tree.py --model='mapo' --name='mapo'
@inproceedings{hong2021weakly,
title = {Learning by Fixing: Solving Math Word Problems with Weak Supervision},
author = {Hong, Yining and Li, Qing and Ciao, Daniel and Huang, Siyuan and Zhu, Song-Chun},
booktitle = {Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, {AAAI-21}},
year = {2021}
}
@inproceedings{Li2020ClosedLN,
title={Closed Loop Neural-Symbolic Learning via Integrating Neural Perception, Grammar Parsing, and Symbolic Reasoning},
author={Qing Li and Siyuan Huang and Yining Hong and Y. Chen and Y. Wu and S. Zhu},
journal={Proceedings of the Thirty-eighth International Conference on Machine Learning},
year={2020}
}