@InProceedings{rush:2018:NLP-OSS,
  author    = {Rush, Alexander},
  title     = {The Annotated Transformer},
  booktitle = {Proceedings of Workshop for NLP Open Source Software (NLP-OSS)},
  month     = {July},
  year      = {2018},
  address   = {Melbourne, Australia},
  publisher = {Association for Computational Linguistics},
  pages     = {52--60},
  abstract  = {(Note this is not being submitted blind. The chair of the workshop requested this submission unblinded from me on twitter, so assuming that is okay.) A major goal of open-source NLP is to quickly and accurately reproduce the results of new work, in a manner that the community can easily use and modify. While most papers publish enough detail for replication, it still may be difficult to achieve good results in practice. This paper presents a worked exercise of paper reproduction with the goal of implementing the results of the recent Transformer model. The replication exercise aims at simple code structure that follows closely with the original work, while achieving an efficient usable system.},
  url       = {http://www.aclweb.org/anthology/W18-2509}
}