While those methods may hold accurate information in their input recovery, they have two main drawbacks: (i) they are computationally expensive: the first method requires training a model for each latent representation, and the second relies on backpropagation for each submitted sentence; (ii) they are highly hyperparameter dependent and may require some finetuning depending on the task at hand.
this is a simple but strong method for analyzing features of text.