What inductive bias does mixup introduce?

Standard mixup samples two examples and forms convex combinations of both their inputs and labels. What behavior does this most directly encourage?

Sparse gradients for examples near the decision boundary

Approximately linear predictive behavior between training examples

Invariance to every transformation preserving the class label

Maximum-margin separation in the original feature space