A Survey on Natural Language Counterfactual Generation

Understand

Natural language counterfactual generation aims to minimally modify a given text such that the modified text will be classified into a different class.

• The generated counterfactuals provide insight into the reasoning behind a model's predictions by highlighting which words significantly influence the outcomes.
• Additionally, they can be used to detect model fairness issues and augment the training data to enhance the model's robustness.
• A substantial amount of research has been conducted to generate counterfactuals for various NLP tasks, employing different models and methodologies.