ARNOR aims to train a neural model which is able to clearly explain the relation patterns through Attention Regularization (AR), and at the same time reduce noise based on an assumption: the clearer the model explain the relation in an instance, the more trustable this instance is.
our ARNOR framework iteratively learns the interpretable model and selects trustable instances.