Awesome work!!!! curious how you handle paragraphs and niche language like federal regulations.
What are your favorite ways to do sentence and paragraph embeddedings and is there a framework you like where you can tune to custom data? Do you find fine tuning your embedding model helpful?
In your review, did you suggest the definition and explanation that they used? In this situation, would have an acknowledgment at the end have been enough? In my mind, it seems like you all had a conversation and the authors took up your suggestions as the reviewer.
Thank you for sharing and releasing usable code! Do you know if this would work for GPU based applications? Tensorflow models that are trained on a GPU, for example?
Do you know of any interesting natural ismorphism between the categories you define in your paper and the category of finite-dimensional hilbert spaces? Curious if you have thought about applications to categorical quantum mechanics.