Training a classifier with text and numerical features - what is the state of the art?
Regarding the first question, to the best of my knowledge, there is no SOTA approach. It depends on the task.

For the second one, did you try to combine the numerical values with the TFIDF vectors, and then feed the final vector(s) to the classifier? Probably not. I usually try this way. But, if your vocabulary is too large, try to reduce it by considering top N-words, because combining small numerical vector with a huge TFIDF vector may not allow the numerical values to affect the results.