English

Russian Texts Detoxification with Levenshtein Editing

Computation and Language 2022-06-10 v2 Machine Learning

Abstract

Text detoxification is a style transfer task of creating neutral versions of toxic texts. In this paper, we use the concept of text editing to build a two-step tagging-based detoxification model using a parallel corpus of Russian texts. With this model, we achieved the best style transfer accuracy among all models in the RUSSE Detox shared task, surpassing larger sequence-to-sequence models.

Cite

@article{arxiv.2204.13638,
  title  = {Russian Texts Detoxification with Levenshtein Editing},
  author = {Ilya Gusev},
  journal= {arXiv preprint arXiv:2204.13638},
  year   = {2022}
}

Comments

Accepted to Dialogue 2022

R2 v1 2026-06-24T11:01:46.951Z