Title
Extractive Adversarial Networks: High-Recall Explanations for Identifying Personal Attacks in Social Media Posts.
Abstract
We introduce an adversarial method for producing high-recall explanations of neural text classifier decisions. Building on an existing architecture for extractive explanations via hard attention, we add an adversarial layer which scans the residual of the attention for remaining predictive signal. Motivated by the important domain of detecting personal attacks in social media comments, we additionally demonstrate the importance of manually setting a semantically appropriate `defaultu0027 behavior for the model by explicitly manipulating its bias term. We develop a validation set of human-annotated personal attacks to evaluate the impact of these changes.
Year
Venue
DocType
2018
EMNLP
Journal
Volume
Citations 
PageRank 
abs/1809.01499
2
0.37
References 
Authors
0
3
Name
Order
Citations
PageRank
Samuel Carton161.57
Qiaozhu Mei24395207.09
Paul Resnick33483563.15