Ranasinghe, Tharindu and Zampieri, Marcos (2021). MUDES: Multilingual Detection of Offensive Spans. IN: NAACL: North American Chapter of the Association for Computational Linguistics. Association for Computational Linguistics (ACL).
Abstract
The interest in offensive content identification in social media has grown substantially in recent years. Previous work has dealt mostly with post level annotations. However, identifying offensive spans is useful in many ways. To help coping with this important challenge, we present MUDES, a multilingual system to detect offensive spans in texts. MUDES features pre-trained models, a Python API for developers, and a user-friendly web-based interface. A detailed description of MUDES’ components is presented in this paper.
| Publication DOI: | https://doi.org/10.18653/v1/2021.naacl-demos.17 |
|---|---|
| Additional Information: | ACL materials are Copyright © 1963–2023 ACL; Materials published in or after 2016 are licensed on a Creative Commons Attribution 4.0 International License. |
| Event Title: | 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations |
| Event Type: | Other |
| Event Location: | online |
| Event Dates: | 2021-06-06 - 2021-06-11 |
| Last Modified: | 29 Oct 2024 16:55 |
| Date Deposited: | 24 Jan 2023 16:09 |
| Full Text Link: |
https://www.len ... 626-734-968-800 https://aclanth ... naacl-demos.17/ |
| Related URLs: | PURE Output Type: | Conference contribution |
| Published Date: | 2021-06 |
| Authors: |
Ranasinghe, Tharindu
(
0000-0003-3207-3821)
Zampieri, Marcos |
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)