For the second challenge, we propose a stochastic sampling scheme to balance teacher-forcing and student-forcing during training, so that the agent can recover from its own mistakes at inference time.
of combining both techniques, on the R2R benchmark test set, our agent (PRESS) 3 achieves 53% on SPL, an absolute 6% gain over the current state of the art.