mlsanityData to 7 Oct 2026

Kungfupanda at SemEval-2020 Task 12: BERT-Based Multi-Task Learning for Offensive Language Detection

arXiv 2004.13432 ↗First posted 28 Apr 2020cs.CL cs.LGcited by 12

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Abstract (arXiv)

Nowadays, offensive content in social media has become a serious problem, and automatically detecting offensive language is an essential task. In this paper, we build an offensive language detection system, which combines multi-task learning with BERT-based models. Using a pre-trained language model such as BERT, we can effectively learn the representations for noisy text in social media. Besides, to boost the performance of offensive language detection, we leverage the supervision signals from other related tasks. In the OffensEval-2020 competition, our model achieves 91.51% F1 score in English Sub-task A, which is comparable to the first place (92.23%F1). An empirical analysis is provided to explain the effectiveness of our approaches.

Key facts. Cited by 12 papers in the map (data through 7 Oct 2026). First posted on arXiv 28 Apr 2020.

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Citing papers per year: 2021: 5; 2022: 2; 2023: 1; 2024: 1; 2025: 2; 2026: 1.

12 papers.