Gulu at SemEval-2021 Task 7: Detecting and Rating Humor and Offense

Maoqin Yang


Abstract
Humor recognition is a challenging task in natural language processing. This document presents my approaches to detect and rate humor and offense from the given text. This task includes 2 tasks: task 1 which contains 3 subtasks (1a, 1b, and 1c), and task 2. Subtask 1a and 1c can be regarded as classification problems and take ALBERT as the basic model. Subtask 1b and 2 can be viewed as regression issues and take RoBERTa as the basic model.
Anthology ID:
2021.semeval-1.156
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:
1120–1124
Language:
URL:
https://aclanthology.org/2021.semeval-1.156
DOI:
10.18653/v1/2021.semeval-1.156
Bibkey:
Cite (ACL):
Maoqin Yang. 2021. Gulu at SemEval-2021 Task 7: Detecting and Rating Humor and Offense. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 1120–1124, Online. Association for Computational Linguistics.
Cite (Informal):
Gulu at SemEval-2021 Task 7: Detecting and Rating Humor and Offense (Yang, SemEval 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.156.pdf