Hi, congratulations on the great tool! I'm wondering if EVO can be used to predict the effect of long variation like large deletion or repeat expansion, since it works well on long input. In such cases, the sequence for alt and ref would have very different lengths. Does this impact the likelihood score and require additional normalization? I think one workaround for the varying sequence length is to generate sequences from healthy cohorts of the same position, each carrying likely neutral variants and are of different length, and use their likelihood score to form a null distribution. Does this approach break any assumption of the EVO2 model? Thanks for your help!