IOT: Instance-wise Layer Reordering for Transformer Structures
Jinhua Zhu,
Lijun Wu,
Yingce Xia
et al.
Abstract:With sequentially stacked self-attention, (optional) encoder-decoder attention, and feed-forward layers, Transformer achieves big success in natural language processing (NLP), and many variants have been proposed. Currently, almost all these models assume that the layer order is fixed and kept the same across data samples. We observe that different data samples actually favor different orders of the layers. Based on this observation, in this work, we break the assumption of the fixed layer order in Transformer… Show more
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