This may be explained by the soft-attention mechanism encouraging the encoder to encode positional information in the input representations, which may help it to predict better attention scores, and to avoid collisions when computing the weighted sum of representations for the context vector.
our hardattention model has other means of obtaining the position information in the decoder using the step actions, and for that reason it does not encode it as strongly in the representations of the inputs.