In other words, our model automatically learns that the convex timedecay attention is more suitable for modeling contexts from the dialogue data than the other two types.
we can conclude that in complex dialogues, the recent utterances contain majority of salient information for spoken language understanding, where the attention decay trend follows a convex curve.