Feb. 13, 2024, 5:49 a.m. | Sourabrata Mukherjee Akanksha Bansal Atul Kr. Ojha John P. McCrae Ond\v{r}ej Du\v{s}ek

cs.CL updates on arXiv.org arxiv.org

This paper focuses on text detoxification, i.e., automatically converting toxic text into non-toxic text. This task contributes to safer and more respectful online communication and can be considered a Text Style Transfer (TST) task, where the text style changes while its content is preserved. We present three approaches: knowledge transfer from a similar task, multi-task learning approach, combining sequence-to-sequence modeling with various toxicity classification tasks, and, delete and reconstruct approach. To support our research, we utilize a dataset provided by …

communication cs.cl english hindi knowledge paper style style transfer text text style transfer transfer

AI Research Scientist

@ Vara | Berlin, Germany and Remote

Data Architect

@ University of Texas at Austin | Austin, TX

Data ETL Engineer

@ University of Texas at Austin | Austin, TX

Lead GNSS Data Scientist

@ Lurra Systems | Melbourne

Data Science Analyst

@ Mayo Clinic | AZ, United States

Sr. Data Scientist (Network Engineering)

@ SpaceX | Redmond, WA