In my experience working with the reviewers (MIS field), important controls, especially if they are (a) emphasized in the prior literature (including theoretical aspects), and (b) available for the researcher, have to be included in the model even if you are not interested in them. Otherwise, it "raises a flag" for them. For instance, what if your variable of interest looses significance or changes sign, in case that control is included?

I'd assume that if the estimates for the predictors of interest are robust to inclusion/exclusion of the controls, then you can omit the ones you are not interested in (yet, mentioning that you checked the robustness). Additionally, I'd examine the correlations between the predicted values for full and reduced models.