Attention Methods for Uncertainty Detection

Introduction

The code provided at this page was used to do the experiments presented in [1] (pdf).

It is written in Theano [2] and Blocks [3].

Resources

Github

Code only: attention_for_uncertainty.zip

Code and preprocessed data: attention_for_uncertainty_withData.zip

For details on running the code, please see Readme.

Cite

If you use the provided code in your work, please cite the following paper:

@inproceedings{adelAttentionUncertainty2016,
  title={Exploring Different Dimensions of Attention for Uncertainty Detection},
  author={Heike Adel and Hinrich Sch\"{u}tze},
  year={2017},
  booktitle={{EACL} 2017, European Chapter of the Association for Computational Linguistics,
               Valencia, Spain, April 3 - April 7, 2017}
}

References

[1] Heike Adel and Hinrich Schütze: "Exploring Different Dimensions of Attention for Uncertainty Detection", EACL 2017.

[2] Theano Development Team: "Theano: A Python framework for fast computation of mathematical expressions", arXiv preprint arXiv:1605.02688, 2016.

[3] Bart van Merriënboer, Dzmitry Bahdanau, Vincent Dumoulin, Dmitriy Serdyuk, David Warde-Farley, Jan Chorowski, and Yoshua Bengio, "Blocks and Fuel: Frameworks for deep learning," arXiv preprint arXiv:1506.00619, 2015

Contact: Heike Adel (website)