Autor:	Gusev, Ilya
Rok vydání:	2022
Předmět:	Computer Science - Computation and Language Computer Science - Machine Learning
Druh dokumentu:	Working Paper
Popis:	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. Comment: Accepted to Dialogue 2022
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2204.13638 Zobrazit plný text záznamu View this record from Arxiv