Review for NeurIPS paper: Stochastic Recursive Gradient Descent Ascent for Stochastic Nonconvex-Strongly-Concave Minimax Problems

What is the lower-bound the paper refer to? - Currently the way that the paper is written does not highlight the novelties of the work. It seems the work combines existing methods for solving min-max with exiting variance reduction modules inside. Please clarify the novelties in the analysis further (the explanation in section 5 does not highlight the difficulties and challenges).