Learning Explanations from Language Data

David Harbecke, Robert Schwarzenberg, Christoph Alt


Abstract
PatternAttribution is a recent method, introduced in the vision domain, that explains classifications of deep neural networks. We demonstrate that it also generates meaningful interpretations in the language domain.
Anthology ID:
W18-5434
Volume:
Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP
Month:
November
Year:
2018
Address:
Brussels, Belgium
Editors:
Tal Linzen, Grzegorz Chrupała, Afra Alishahi
Venue:
EMNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
316–318
Language:
URL:
https://aclanthology.org/W18-5434
DOI:
10.18653/v1/W18-5434
Bibkey:
Cite (ACL):
David Harbecke, Robert Schwarzenberg, and Christoph Alt. 2018. Learning Explanations from Language Data. In Proceedings of the 2018 EMNLP Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, pages 316–318, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):
Learning Explanations from Language Data (Harbecke et al., EMNLP 2018)
Copy Citation:
PDF:
https://aclanthology.org/W18-5434.pdf
Code
 DFKI-NLP/language-attributions