On the other hand, self-attention-based AT-TOrderNet (encoder side) and attention-based our TGCM/TGCM-S (decoder side) use a set of sentence representations in a permutation-invariant manner rather than a single vector to represent a paragraph.
these models can capture global dependencies regardless of the order of input sentences.