FixMatch with MixUp

[Ryoo72]

Thanks for the great research. Can I ask you a question? The paper said "One may replace strong augmentation in FixMatch modality-agnostic augmentation strategies, such as MixUp". I can't understand this part well. I am curious about the specific way MixUp was used in FixMatch.
For example, If there are two unlabeled data, FixMatch mixes up two data with 0.4:0.6 ratio. And FixMatch gives consistency loss between Pseudo-label and prediction. So, Ideal weakly Augmented model prediction should be [..., 0.4, 0.6, ...]. Am I right? Thanks for reading.