Building competitive self-explaining NLP models — Introduction Model interpretability is crucial if we want to use AI models to make high-stake decisions (e.g., making medical diagnoses, preventing suicides, etc.). In NLP, one common way to get interpretability is to extract information from the trained models. For example, some use gradient-based input attribution techniques, some perturb the input…