Clarify: Improving Model Robustness With Natural Language Corrections

Understand

The standard way to teach models is by feeding them lots of data.

• However, this approach often teaches models incorrect ideas because they pick up on misleading signals in the data.
• To prevent such misconceptions, we must necessarily provide additional information beyond the training data.
• Prior methods incorporate additional instance-level supervision, such as labels for misleading features or additional labels for debiased data.