They trained a new noise-aware one on the same dataset, I believe. The CLIP is frozen though in the second stage where they train on a cleaner dataset for the i

They trained a new noise-aware one on the same dataset, I believe. The CLIP is frozen though in the second stage where they train on a cleaner dataset for the image generation via diffusion conditioned on a CLIP image embed. They get the image embed from another model that can predict image embeds from text embeds to encourage generalizing when sampling. It does suffer from some of the same issues with binding attributes and counting stuff, as far as I can tell. But that's not necessarily related to its ability to compose concepts.