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
- Venue:
- SemEval
- SIGs:
- SIGLEX | SIGSEM
- 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
- Cite (ACL):
- Hamed Babaei Giglou, Taher Rahgooy, Mostafa Rahgouy, and Jafar Razmara. 2021. UoT-UWF-PartAI at SemEval-2021 Task 5: Self Attention Based Bi-GRU with Multi-Embedding Representation for Toxicity Highlighter. In Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021), pages 948–952, Online. Association for Computational Linguistics.
- Cite (Informal):
- UoT-UWF-PartAI at SemEval-2021 Task 5: Self Attention Based Bi-GRU with Multi-Embedding Representation for Toxicity Highlighter (Babaei Giglou et al., SemEval 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.semeval-1.129.pdf