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Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Humor and Offense are highly subjective due to multiple word senses, cultural knowledge, and pragmatic competence. Hence, accurately detecting humorous and offensive texts has several compelling use cases in Recommendation Systems and Personalized Content Moderation. However, due to the lack of an extensive labeled dataset, most prior works in this domain haven't explored large neural models for subjective humor understanding. This paper explores whether large neural models and their ensemblesdoi:10.18653/v1/2021.semeval-1.36 fatcat:5qo3mhdpvjakdiegeuqooorvcq