UoT-UWF-PartAI at SemEval-2021 Task 5: Self Attention Based Bi-GRU with Multi-Embedding Representation for Toxicity Highlighter

Hamed Babaei Giglou, Taher Rahgooy, Mostafa Rahgouy, Jafar Razmara


Abstract
Toxic Spans Detection(TSD) task is defined as highlighting spans that make a text toxic. Many works have been done to classify a given comment or document as toxic or non-toxic. However, none of those proposed models work at the token level. In this paper, we propose a self-attention-based bidirectional gated recurrent unit(BiGRU) with a multi-embedding representation of the tokens. Our proposed model enriches the representation by a combination of GPT-2, GloVe, and RoBERTa embeddings, which led to promising results. Experimental results show that our proposed approach is very effective in detecting span tokens.
Anthology ID:
2021.semeval-1.129
Volume:
Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
Month:
August
Year:
2021
Address:
Online
Venues:
ACL | IJCNLP | SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
948–952
Language:
URL:
https://aclanthology.org/2021.semeval-1.129
DOI:
10.18653/v1/2021.semeval-1.129
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/2021.semeval-1.129.pdf