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Detect All Abuse! Toward Universal Abusive Language Detection Models

Detect All Abuse! Toward Universal Abusive Language Detection Models

8 October 2020
Kunze Wang
Dong Lu
S. Han
Siqu Long
Josiah Poon
ArXivPDFHTML

Papers citing "Detect All Abuse! Toward Universal Abusive Language Detection Models"

6 / 6 papers shown
Title
A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
A Multi-Task Benchmark for Abusive Language Detection in Low-Resource Settings
Fitsum Gaim
Hoyun Song
Huije Lee
Changgeon Ko
Eui Jun Hwang
Jong C. Park
19
0
0
17 May 2025
MC-DRE: Multi-Aspect Cross Integration for Drug Event/Entity Extraction
MC-DRE: Multi-Aspect Cross Integration for Drug Event/Entity Extraction
Jie Yang
S. Han
Siqu Long
Josiah Poon
Goran Nenadic
50
0
0
12 Aug 2023
K-MHaS: A Multi-label Hate Speech Detection Dataset in Korean Online
  News Comment
K-MHaS: A Multi-label Hate Speech Detection Dataset in Korean Online News Comment
Jean Lee
Taejun Lim
Hee-Youn Lee
Bogeun Jo
Yangsok Kim
Heegeun Yoon
S. Han
24
19
0
23 Aug 2022
Detecting Harmful Online Conversational Content towards LGBTQIA+
  Individuals
Detecting Harmful Online Conversational Content towards LGBTQIA+ Individuals
Jamell Dacon
Harry Shomer
Shaylynn Crum-Dacon
Jiliang Tang
32
8
0
15 Jun 2022
ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in
  Conversational AI
ConvAbuse: Data, Analysis, and Benchmarks for Nuanced Abuse Detection in Conversational AI
Amanda Cercas Curry
Gavin Abercrombie
Verena Rieser
34
79
0
20 Sep 2021
Anticipating Safety Issues in E2E Conversational AI: Framework and
  Tooling
Anticipating Safety Issues in E2E Conversational AI: Framework and Tooling
Emily Dinan
Gavin Abercrombie
A. S. Bergman
Shannon L. Spruit
Dirk Hovy
Y-Lan Boureau
Verena Rieser
43
105
0
07 Jul 2021
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