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DRGA： deep reinforcement learning guided attention

This repository includes the code of the paper Optimizing attention for sequence modeling via reinforcement learning published at IEEE TNNLS.

Requirement

python>=3.6
tensorflow
tflearn
numpy

Datasets

Text classifications:

  • Movie Review (MR)
  • AGnews
  • Subjectivity (SUBJ)
  • Stanford Sentiment Treebank (SST)

Word embedding

prepare the glove word embedding at emb file:

glove.6B.100d.txt

Running

python core/main.py

Citation

If you use this work, please kindly cite:

@article{FeiZRJ22,
  author       = {Hao Fei and
                  Yue Zhang and
                  Yafeng Ren and
                  Donghong Ji},
  title        = {Optimizing Attention for Sequence Modeling via Reinforcement Learning},
  journal      = {{IEEE} Trans. Neural Networks Learn. Syst.},
  volume       = {33},
  number       = {8},
  pages        = {3612--3621},
  year         = {2022},
  url          = {https://doi.org/10.1109/TNNLS.2021.3053633}
}

License

The code is released under Apache License 2.0 for Noncommercial use only.