Learning to Faithfully Rationalize by Construction

Understand

In many settings it is important for one to be able to understand why a model made a particular prediction.

• In NLP this often entails extracting snippets of an input text `responsible for' corresponding model output; when such a snippet comprises tokens that indeed informed the model's prediction, it is a faithful explanation.
• In some settings, faithfulness may be critical to ensure transparency.
• Lei et al.