mlsanityData to 7 Oct 2026

MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection

arXiv 2104.04739 ↗First posted 10 Apr 2021cs.CL cs.AI cs.IRcited by 1

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Abstract (arXiv)

This paper describes our system for SemEval-2021 Task 5 on Toxic Spans Detection. We developed ensemble models using BERT-based neural architectures and post-processing to combine tokens into spans. We evaluated several pre-trained language models using various ensemble techniques for toxic span identification and achieved sizable improvements over our baseline fine-tuned BERT models. Finally, our system obtained a F1-score of 67.55% on test data.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 17 of its 38 references that are in the map. First posted on arXiv 10 Apr 2021.

Builds on

17 of 38 references.

References · 17

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5 more
  1. 2017One-step and Two-step Classification for Abusive Language Detection on Twittercited by 46
  2. 2020Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysiscited by 45
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Citing papers per year: 2023: 1.

1 paper.

  1. 2023ViHOS: Hate Speech Spans Detection for Vietnamesecited by 13