Review for NeurIPS paper: CoSE: Compositional Stroke Embeddings

Weaknesses: The rebuttal and discussion clarified my concerns about [1,2] (although I would highly encourage that these works be citied for a more complete related works section). However, I remain unconvinced by the novelty of the approach -- the fact that transformer based models work better compared to simple VAE based models is not surprising to the general NeurIPS audience. However, I do agree that from the point of view of stroke based generative models the work is novel and makes a good contribution to this specific field. Novelty wrt to [1] is not clear -- both methods use a transformer based architecture to model long-range dependencies in strokes. The advantage of an autoregressive structure along with transformers is not clear as transformers contain self-attention layers to capture long range dependencies.