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

• URL: http://arxiv.org/abs/2104.13164v1
• Date: Tue, 27 Apr 2021 13:18:28 GMT
• Title: UoT-UWF-PartAI at SemEval-2021 Task 5: Self Attention Based Bi-GRU with Multi-Embedding Representation for Toxicity Highlighter
• Authors: Hamed Babaei Giglou, Taher Rahgooy, Mostafa Rahgouy and Jafar Razmara
• Abstract summary: We propose a self-attention-based gated recurrent unit with a multi-embedding representation of the tokens. Experimental results show that our proposed approach is very effective in detecting span tokens.
• Score: 3.0586855806896045
• License: http://creativecommons.org/licenses/by-sa/4.0/
• 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.

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