most citedBLISS: Robust Sequence-to-Sequence Learning via Self-Supervised Input Representation

9 citations · 9 across the 1 of their papers we have counts for

collaborators

1 paper

cs.CL2022★ 9 cited

BLISS: Robust Sequence-to-Sequence Learning via Self-Supervised Input Representation

Zheng Zhang, Liang Ding, Dazhao Cheng +3

Data augmentations (DA) are the cores to achieving robust sequence-to-sequence learning on various natural language processing (NLP) tasks. However, most of the DA approaches force…