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ToKen: Task Decomposition and Knowledge Infusion for Few-Shot Hate Speech Detection. (arXiv:2205.12495v1 [cs.CL])
May 26, 2022, 1:12 a.m. | Badr AlKhamissi, Faisal Ladhak, Srini Iyer, Ves Stoyanov, Zornitsa Kozareva, Xian Li, Pascale Fung, Lambert Mathias, Asli Celikyilmaz, Mona Diab
cs.CL updates on arXiv.org arxiv.org
Hate speech detection is complex; it relies on commonsense reasoning,
knowledge of stereotypes, and an understanding of social nuance that differs
from one culture to the next. It is also difficult to collect a large-scale
hate speech annotated dataset. In this work, we frame this problem as a
few-shot learning task, and show significant gains with decomposing the task
into its "constituent" parts. In addition, we see that infusing knowledge from
reasoning datasets (e.g. Atomic2020) improves the performance even further. …
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