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  1. traditional seq2seq model is trained by teacher-forcing, which is totally different during inference.
  2. In order to optimize the test score (i.e., BLEU or word-error-rate), they propose to sampling $y_t$ during training to minimise the gap between training and testing.
  3. the sampling function they propose is $\exp$ family that decreased with time, other forms of sampling strategy is not tried. (important!)


  • Scheduled sampling for sequence prediction with recurrent neural networks.