https://github.com/xingdi-eric-yuan/qait_public

Question Answering with Interactive Text (QAit), code for EMNLP 2019 paper "Interactive Language Learning by Question Answering"
https://github.com/xingdi-eric-yuan/qait_public

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Question Answering with Interactive Text (QAit), code for EMNLP 2019 paper "Interactive Language Learning by Question Answering"

• Host: GitHub
• URL: https://github.com/xingdi-eric-yuan/qait_public
• Owner: xingdi-eric-yuan
• License: mit
• Created: 2019-08-21T19:46:44.000Z (over 5 years ago)
• Default Branch: master
• Last Pushed: 2019-09-03T03:43:46.000Z (over 5 years ago)
• Last Synced: 2024-11-13T14:39:28.027Z (2 months ago)
• Language: Python
• Size: 80.1 KB
• Stars: 44
• Watchers: 4
• Forks: 9
• Open Issues: 1
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Interactive Language Learning by Question Answering

--------------------------------------------------------------------------------

Code for EMNLP 2019 paper "Interactive Language Learning by Question Answering".

## To install dependencies

```

sudo apt update

conda create -p ~/venvs/qait python=3.6

source activate ~/venvs/qait

pip install --upgrade pip

pip install numpy==1.16.4

pip install https://github.com/Microsoft/TextWorld/archive/rebased-interactive-qa.zip

pip install -U spacy

python -m spacy download en

pip install tqdm h5py visdom pyyaml

conda install pytorch torchvision cudatoolkit=9.2 -c pytorch

```

## Test Set

Download the test set from [https://aka.ms/qait-testset](https://aka.ms/qait-testset). Unzip it.

## Pretrained Word Embeddings

Before first time running it, download fasttext crawl-300d-2M.vec.zip from [HERE](https://fasttext.cc/docs/en/english-vectors.html), unzip, and run [embedding2h5.py](./embedding2h5.py) for fast embedding loading in the future.

## To Train

```

python train.py ./

```

## Citation

Please use the following bibtex entry:

```

@article{yuan2019qait,

  title={Interactive Language Learning by Question Answering},

  author={Yuan, Xingdi and C\^ot\'{e}, Marc-Alexandre and Fu, Jie and Lin, Zhouhan and Pal, Christopher and Bengio, Yoshua and Trischler, Adam},

  booktitle={EMNLP},

  year={2019}

}

```

## License

[MIT](./LICENSE)