  Transformers have achieved great success in many artificial intelligence
fields, such as natural language processing, computer vision, and audio
processing. Therefore, it is natural to attract lots of interest from academic
and industry researchers. Up to the present, a great variety of Transformer
variants (a.k.a. X-formers) have been proposed, however, a systematic and
comprehensive literature review on these Transformer variants is still missing.
In this survey, we provide a comprehensive review of various X-formers. We
first briefly introduce the vanilla Transformer and then propose a new taxonomy
of X-formers. Next, we introduce the various X-formers from three perspectives:
architectural modification, pre-training, and applications. Finally, we outline
some potential directions for future research.
