metadata
license: apache-2.0
language:
- en
infiniterik/desc-detoxify-sicon
Fine-tuned instance of T5-Large for detoxifying discourse surrounding abortion debate. Implementation and ethical considerations are listed in the paper Detoxifying Online Discourse: A Guided Response Generation Approach for Reducing Toxicity in User-Generated Text.
Github repository can be found here.
Citation
BibTeX:
@inproceedings{bose-etal-2023-detoxifying,
title = "Detoxifying Online Discourse: A Guided Response Generation Approach for Reducing Toxicity in User-Generated Text",
author = "Bose, Ritwik and Perera, Ian and Dorr, Bonnie",
booktitle = "Proceedings of the First Workshop on Social Influence in Conversations (SICon 2023)",
month = jul,
year = "2023",
address = "Toronto, Canada",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.sicon-1.2",
pages = "9--14"
}