Their comparison against PolyGen looks like it's a big improvement. What are the limitations that this has in common with PolyGen that make it still not useful?
I don’t think it’s as widely applicable as they try to make it seem. I have worked specifically with PolyGen, and the main problem is “out of distribution” data. Basically anything you want to do will likely be outside the training distribution. This surfaces as sequencing. How do you determine which triangle or vertex to place first? Why would a user do it that way? What if I want to draw a table with the legs last? Cannot be done. The model is autoregressive.
First, you use the word "transformers" to mean "autoregressive models", they are not synonymous, second, this model beats Polygen on every metric, it's not even close.
