Here, we propose a novel approach based on scheduled sampling that uses a differentiable approximation of previous greedy decoding decisions inside the training objective by incorporating a continuous relaxation of argmax.
our end-to-end relaxed greedy training objective is differentiable everywhere and fully continuous.