It may not be known yet, and this project seems to be targeted at gaussian distributions, but wouldn't the simplicity bias reduce sensitivity? I mean attention

It may not be known yet, and this project seems to be targeted at gaussian distributions, but wouldn't the simplicity bias reduce sensitivity? I mean attention in transformers works so well in part because OOD is typically close enough. Probably just my own bias because it seems everything I deal with is at least MArP and anomalies are important to my use case. I can see where this is useful for others, even Amazon suggests ARIMA or ETS if you don't have hundreds of related streams. Is this more targeted at people who want more smoothing? Or am I just missing something?