DYLE_pytorch-lightning

Reproduction of source code for ACL 2022 paper DYLE using Pytorch-Lightning: Dynamic latent extraction for abstract long input summary

Folder Structure

• dataloaders: the python scripts to convert original dataset to the uniform format.
• oracle: Scripts to generate extractive oracles
• utils: Various utility functions, such as cleaning and rouge
• config.py: Set model configuration
• Modules: Contains implementation of our dynamic extraction module
• main.py: Train the model

Training and Evaluation

Download the Datasets and Models

• Download QMSum dataset from https://github.com/Yale-LILY/QMSum
• Using Pyrouge Metric from https://github.com/bheinzerling/pyrouge

Training

  python main.py --gpus -1 --distributed_backend dp

References

DYLE

Citation

@inproceedings{mao2021dyle,
  title={DYLE: Dynamic Latent Extraction for Abstractive Long-Input Summarization},
  author={Mao, Ziming and Wu, Chen Henry and Ni, Ansong and Zhang, Yusen and Zhang, Rui and Yu, Tao and Deb, Budhaditya and Zhu, Chenguang and Awadallah, Ahmed H and Radev, Dragomir},
  booktitle={ACL 2022},
  year={2022}
}