[D] NLP models with output in the embedding space? • r/MachineLearning

I am interested in knowing if there are any publications that propose models where the output is not a softmax but a vector in the embedding space or, alternatively, suggestions on how to do it, like what loss function to use (e.g. MSE between output and expected embedded vectors) or not to use, and why. I have not been able to find anything in google or google scholar, that's why I resort to the knowledge of this subreddit. I would appreciate any help.