The HN submission title is editorialized in a non-helpful way. Why beat a dead horse instead of focusing on what’s actually new in TFA?
The linked paper proposes an obvious-in-retrospect form of data augmentation: shuffle the order of the premises, so that the model can’t rely on spurious patterns. That’s kinda neat.
Comments
The HN submission title is editorialized in a non-helpful way. Why beat a dead horse instead of focusing on what’s actually new in TFA?
The linked paper proposes an obvious-in-retrospect form of data augmentation: shuffle the order of the premises, so that the model can’t rely on spurious patterns. That’s kinda neat.
Correct, I updated the title of the original paper. Thank you your bringing up.