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MUDES: Multilingual Detection of Offensive Spans

arXiv 2102.09665 ↗First posted 18 Feb 2021cs.CL cs.AI cs.LGcited by 30

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Abstract (arXiv)

The interest in offensive content identification in social media has grown substantially in recent years. Previous work has dealt mostly with post level annotations. However, identifying offensive spans is useful in many ways. To help coping with this important challenge, we present MUDES, a multilingual system to detect offensive spans in texts. MUDES features pre-trained models, a Python API for developers, and a user-friendly web-based interface. A detailed description of MUDES' components is presented in this paper.

Key facts. Cited by 30 papers in the map (data through 7 Oct 2026). Builds on 31 of its 52 references that are in the map. First posted on arXiv 18 Feb 2021.

Builds on

31 of 52 references.

References · 31

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
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  11. 2019Predicting the Type and Target of Offensive Posts in Social Mediacited by 268
  12. 2019SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)cited by 206
19 more
  1. 2020SemEval-2020 Task 12: Multilingual Offensive Language Identification in Social Media (OffensEval 2020)cited by 138
  2. 2019Fine-Grained Analysis of Propaganda in News Articlescited by 130
  3. 2020Multilingual Offensive Language Identification with Cross-lingual Embeddingscited by 71
  4. 2020SOLID: A Large-Scale Semi-Supervised Dataset for Offensive Language Identificationcited by 53
  5. 2020Offensive Language Identification in Greekcited by 49
  6. 2019Offensive Language and Hate Speech Detection for Danishcited by 48
  7. 2017Detecting Hate Speech in Social Mediacited by 42
  8. 2020Arabic Offensive Language on Twitter: Analysis and Experimentscited by 28
  9. 2018Challenges in Discriminating Profanity from Hate Speechcited by 23
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  12. 2020Galileo at SemEval-2020 Task 12: Multi-lingual Learning for Offensive Language Identification using Pre-trained Language Modelscited by 11
  13. 2020BRUMS at SemEval-2020 Task 12 : Transformer based Multilingual Offensive Language Identification in Social Mediacited by 10
  14. 2020UHH-LT at SemEval-2020 Task 12: Fine-Tuning of Pre-Trained Transformer Networks for Offensive Language Detectioncited by 9
  15. 2020InfoMiner at WNUT-2020 Task 2: Transformer-based Covid-19 Informative Tweet Extractioncited by 9
  16. 2020WLV-RIT at HASOC-Dravidian-CodeMix-FIRE2020: Offensive Language Identification in Code-switched YouTube Commentscited by 9
  17. 2020NLPDove at SemEval-2020 Task 12: Improving Offensive Language Detection with Cross-lingual Transfercited by 8
  18. 2020Detecting Online Hate Speech: Approaches Using Weak Supervision and Network Embedding Modelscited by 5
  19. 2020LT@Helsinki at SemEval-2020 Task 12: Multilingual or language-specific BERT?cited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 10; 2022: 5; 2023: 4; 2024: 6; 2025: 3; 2026: 2.

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  1. 2021FBERT: A Neural Transformer for Identifying Offensive Contentcited by 30
  2. 2021Cross-lingual Offensive Language Identification for Low Resource Languages: The Case of Marathicited by 28
  3. 2021Multilingual Offensive Language Identification for Low-resource Languagescited by 22
  4. 2021An Exploratory Analysis of Multilingual Word-Level Quality Estimation with Cross-Lingual Transformerscited by 18
  5. 2021An Exploratory Analysis of the Relation Between Offensive Language and Mental Healthcited by 14
  6. 2022KOLD: Korean Offensive Language Datasetcited by 14
  7. 2021Comparing Approaches to Dravidian Language Identificationcited by 11
  8. 2021WLV-RIT at SemEval-2021 Task 5: A Neural Transformer Framework for Detecting Toxic Spanscited by 6
  9. 2022Predicting the Type and Target of Offensive Social Media Posts in Marathicited by 5
  10. 2021Transformers to Fight the COVID-19 Infodemiccited by 4
  11. 2023Cross-Domain Toxic Spans Detectioncited by 4
  12. 2023Muted: Multilingual Targeted Offensive Speech Identification and Visualizationcited by 4
18 more
  1. 2024A Federated Learning Approach to Privacy Preserving Offensive Language Identificationcited by 4
  2. 2024Fake News Detection: Comparative Evaluation of BERT-like Models and Large Language Models with Generative AI-Annotated Datacited by 4
  3. 2021TransWiC at SemEval-2021 Task 2: Transformer-based Multilingual and Cross-lingual Word-in-Context Disambiguationcited by 3
  4. 2021WLV-RIT at GermEval 2021: Multitask Learning with Transformers to Detect Toxic, Engaging, and Fact-Claiming Commentscited by 3
  5. 2025Evaluating Open-Source Vision-Language Models for Multimodal Sarcasm Detectioncited by 3
  6. 2022Exploring Hate Speech Detection with HateXplain and BERTcited by 2
  7. 2022SOLD: Sinhala Offensive Language Datasetcited by 2
  8. 2023Overview of the HASOC Subtrack at FIRE 2023: Identification of Tokens Contributing to Explicit Hate in English by Span Detectioncited by 2
  9. 2024Cross-lingual Offensive Language Detection: A Systematic Review of Datasets, Transfer Approaches and Challengescited by 2
  10. 2024MasonPerplexity at Multimodal Hate Speech Event Detection 2024: Hate Speech and Target Detection Using Transformer Ensemblescited by 2
  11. 2024A Federated Approach to Few-Shot Hate Speech Detection for Marginalized Communitiescited by 2
  12. 2024Towards Generalized Offensive Language Identificationcited by 1
  13. 2025Language, Culture, and Ideology: Personalizing Offensiveness Detection in Political Tweets with Reasoning LLMscited by 1
  14. 2022Transformer-based Detection of Multiword Expressions in Flower and Plant Namescited by 0
  15. 2023Deep Learning Methods for Extracting Metaphorical Names of Flowers and Plantscited by 0
  16. 2025WATCHED: A Web AI Agent Tool for Combating Hate Speech by Expanding Datacited by 0
  17. 2026Exploring the Performance of Large Language Models on Subjective Span Identification Taskscited by 0
  18. 2026PEACE 2.0: Grounded Explanations and Counter-Speech for Combating Hate Expressionscited by 0