@inproceedings{nikolaev23:_universe,
  abstract = {It has been argued that BERT ``rediscovers the traditional NLP
pipeline'', with lower layers extracting morphosyntactic features and
higher layers creating holistic sentence-level representations.
In this paper, we critically examine this assumption through a
principle-component-guided analysis, extracing sets of inputs that
correspond to specific activation patterns in BERT sentence representations.
We find that even in higher layers, the model mostly picks up on a
variegated bunch of low-level features, many related to sentence
complexity, that presumably arise from its specific pre-training
objectives.},
  added-at = {2023-04-26T18:18:19.000+0200},
  address = {Nancy, France},
  author = {Nikolaev, Dmitry and Padó, Sebastian},
  biburl = {https://puma.ub.uni-stuttgart.de/bibtex/2995882df8792875cb3a67bbea378a90a/sp},
  booktitle = {Proceedings of IWCS},
  interhash = {9dabc394be5ffe8d8b9818192791f99a},
  intrahash = {995882df8792875cb3a67bbea378a90a},
  keywords = {conference myown},
  timestamp = {2024-02-22T12:31:40.000+0100},
  title = {The Universe of Utterances According to {BERT}},
  url = {https://aclanthology.org/2023.iwcs-1.12.pdf},
  year = 2023
}