Papers with transformer-based HAP-classification model

1 papers
Muted: Multilingual Targeted Offensive Speech Identification and Visualization (2023.emnlp-demo)

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Challenge: Existing visualizations of offensive language use only sentence level annotations, but there are few that explore spans and other languages.
Approach: They propose a system to identify multilingual HAP content by displaying offensive arguments and their targets using heat maps to indicate their intensity.
Outcome: The proposed model can identify toxic spans without further fine-tuning using existing models and its attention mechanism out-of-the-box.

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