Chinese researchers are very fond of doing extensive surveys of a particular sub-field of machine learning, listing the main works and the major breakthrough ideas. There are so many articles published every day, and it is impossible to read everything. Therefore, such reviews are valuable (if they are well written, of course, which is quite rare).
Recently there was a very good paper reviewing various variants of Transformers with a focus on language modeling (NLP).
This is a must-read for anyone getting into the world of NLP and interested in Transformers. The paper discusses the basic principles of self-attention and such details of modern variants of Transformers as architecture modifications, pre-training, and various applications.
Paper: A Survey of Transformers.
