IIITH at SemEval-2021 Task 7: Leveraging transformer-based humourous and offensive text detection architectures using lexical and hurtlex features and task adaptive pretraining

Tathagata Raha, Ishan Sanjeev Upadhyay, Radhika Mamidi, Vasudeva Varma


Abstract
This paper describes our approach (IIITH) for SemEval-2021 Task 5: HaHackathon: Detecting and Rating Humor and Offense. Our results focus on two major objectives: (i) Effect of task adaptive pretraining on the performance of transformer based models (ii) How does lexical and hurtlex features help in quantifying humour and offense. In this paper, we provide a detailed description of our approach along with comparisions mentioned above.
Anthology ID:
2021.semeval-1.173
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Editors:
Alexis Palmer, Nathan Schneider, Natalie Schluter, Guy Emerson, Aurelie Herbelot, Xiaodan Zhu
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
1221–1225
Language:
URL:
https://aclanthology.org/2021.semeval-1.173
DOI:
10.18653/v1/2021.semeval-1.173
Bibkey:
Cite (ACL):
Tathagata Raha, Ishan Sanjeev Upadhyay, Radhika Mamidi, and Vasudeva Varma. 2021. IIITH at SemEval-2021 Task 7: Leveraging transformer-based humourous and offensive text detection architectures using lexical and hurtlex features and task adaptive pretraining. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 1221–1225, Online. Association for Computational Linguistics.
Cite (Informal):
IIITH at SemEval-2021 Task 7: Leveraging transformer-based humourous and offensive text detection architectures using lexical and hurtlex features and task adaptive pretraining (Raha et al., SemEval 2021)
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PDF:
https://aclanthology.org/2021.semeval-1.173.pdf