We propose a novel objective function to optimize the entire framework end-to-end, where we focus more on the group-level prediction and take into account multiple important factors.
the objective function explicitly penalizes three potential errors in answer triggering: (1) false-positive and (2) false-negative predictions of the existence of a correct answer, as well as (3) ranking incorrect answers higher than correct ones.