mlsanityData to 7 Oct 2026

Detecting Hate Speech with GPT-3

arXiv 2103.12407 ↗First posted 23 Mar 2021cs.CLcited by 55

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Abstract (arXiv)

Sophisticated language models such as OpenAI's GPT-3 can generate hateful text that targets marginalized groups. Given this capacity, we are interested in whether large language models can be used to identify hate speech and classify text as sexist or racist. We use GPT-3 to identify sexist and racist text passages with zero-, one-, and few-shot learning. We find that with zero- and one-shot learning, GPT-3 can identify sexist or racist text with an average accuracy between 55 per cent and 67 per cent, depending on the category of text and type of learning. With few-shot learning, the model's accuracy can be as high as 85 per cent. Large language models have a role to play in hate speech detection, and with further development they could eventually be used to counter hate speech.

Key facts. Cited by 55 papers in the map (data through 7 Oct 2026). Builds on 11 of its 27 references that are in the map. First posted on arXiv 23 Mar 2021.

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11 of 27 references.

References · 11

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2020Language Models are Few-Shot Learnerscited by 32,199
  4. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  5. 2021Switch Transformers: Scaling to Trillion Parameter Models with Simple and Efficient Sparsitycited by 3,014
  6. 2017Automated Hate Speech Detection and the Problem of Offensive Languagecited by 724
  7. 2021Self-Diagnosis and Self-Debiasing: A Proposal for Reducing Corpus-Based Bias in NLPcited by 336
  8. 2020The Pushshift Reddit Datasetcited by 289
  9. 2019Racial Bias in Hate Speech and Abusive Language Detection Datasetscited by 208
  10. 2020The Radicalization Risks of GPT-3 and Advanced Neural Language Modelscited by 76
  11. 2021Addressing Hate Speech with Data Science: An Overview from Computer Science Perspectivecited by 1

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2021: 3; 2022: 4; 2023: 18; 2024: 15; 2025: 13; 2026: 2.

55 papers.

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  1. 2022OPT: Open Pre-trained Transformer Language Modelscited by 3,464
  2. 2022GLM-130B: An Open Bilingual Pre-trained Modelcited by 837
  3. 2021AI Chains: Transparent and Controllable Human-AI Interaction by Chaining Large Language Model Promptscited by 265
  4. 2024Attacks, Defenses and Evaluations for LLM Conversation Safety: A Surveycited by 124
  5. 2025A Comprehensive Survey in LLM(-Agent) Full Stack Safety: Data, Training and Deploymentcited by 110
  6. 2023AI model GPT-3 (dis)informs us better than humanscited by 75
  7. 2023Tricking LLMs into Disobedience: Formalizing, Analyzing, and Detecting Jailbreakscited by 45
  8. 2023Evaluating GPT-3 Generated Explanations for Hateful Content Moderationcited by 44
  9. 2023Opportunities and Risks of LLMs for Scalable Deliberation with Poliscited by 41
  10. 2023SentimentGPT: Exploiting GPT for Advanced Sentiment Analysis and its Departure from Current Machine Learningcited by 38
  11. 2023You Only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Contentcited by 37
  12. 2023Interpretable Unified Language Checkingcited by 26
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  1. 2024An Investigation of Large Language Models for Real-World Hate Speech Detectioncited by 20
  2. 2023User Modeling in the Era of Large Language Models: Current Research and Future Directionscited by 18
  3. 2023Watch Your Language: Investigating Content Moderation with Large Language Modelscited by 14
  4. 2023Evaluating the Fairness of Discriminative Foundation Models in Computer Visioncited by 12
  5. 2023Causality Guided Disentanglement for Cross-Platform Hate Speech Detectioncited by 9
  6. 2025Analyzing Political Bias in LLMs via Target-Oriented Sentiment Classificationcited by 7
  7. 2023Academic Writing with GPT-3.5: Reflections on Practices, Efficacy and Transparencycited by 6
  8. 2023Generative AI for Hate Speech Detection: Evaluation and Findingscited by 6
  9. 2024Towards Lifelong Scene Graph Generation with Knowledge-ware In-context Prompt Learningcited by 6
  10. 2024MisgenderMender: A Community-Informed Approach to Interventions for Misgenderingcited by 6
  11. 2024LionGuard: Building a Contextualized Moderation Classifier to Tackle Localized Unsafe Contentcited by 5
  12. 2024Recent Advances in Attack and Defense Approaches of Large Language Modelscited by 5
  13. 2024Harnessing Artificial Intelligence to Combat Online Hate: Exploring the Challenges and Opportunities of Large Language Models in Hate Speech Detectioncited by 4
  14. 2024HateCOT: An Explanation-Enhanced Dataset for Generalizable Offensive Speech Detection via Large Language Modelscited by 4
  15. 2024Detection of Conspiracy Theories Beyond Keyword Bias in German-Language Telegram Using Large Language Modelscited by 4
  16. 2025Mario at EXIST 2025: A Simple Gateway to Effective Multilingual Sexism Detectioncited by 4
  17. 2022Leveraging pre-trained language models for conversational information seeking from textcited by 3
  18. 2022Hypothesis Engineering for Zero-Shot Hate Speech Detectioncited by 3
  19. 2025Web-Browsing LLMs Can Access Social Media Profiles and Infer User Demographicscited by 3
  20. 2025HateClipSeg: A Segment-Level Annotated Dataset for Fine-Grained Hate Video Detectioncited by 3
  21. 2023Focal Inferential Infusion Coupled with Tractable Density Discrimination for Implicit Hate Detectioncited by 2
  22. 2024OffensiveLang: A Community Based Implicit Offensive Language Datasetcited by 2
  23. 2025Digital Guardians: Can GPT-4, Perspective API, and Moderation API reliably detect hate speech in reader comments of German online newspapers?cited by 2
  24. 2025Conditioning Large Language Models on Legal Systems? Detecting Punishable Hate Speechcited by 2
  25. 2025Multi-Agent VLMs Guided Self-Training with PNU Loss for Low-Resource Offensive Content Detectioncited by 2
  26. 2021What's in a Measurement? Using GPT-3 on SemEval 2021 Task 8 -- MeasEvalcited by 1
  27. 2021Survey of Generative Methods for Social Media Analysiscited by 1
  28. 2023Evaluating the Effectiveness of Natural Language Inference for Hate Speech Detection in Languages with Limited Labeled Datacited by 1
  29. 2023Is GPT Powerful Enough to Analyze the Emotions of Memes?cited by 1
  30. 2023DRAFT: Dense Retrieval Augmented Few-shot Topic classifier Frameworkcited by 1
  31. 2024Towards Understanding Counseling Conversations: Domain Knowledge and Large Language Modelscited by 1
  32. 2024Leveraging Weakly Annotated Data for Hate Speech Detection in Code-Mixed Hinglish: A Feasibility-Driven Transfer Learning Approach with Large Language Modelscited by 1
  33. 2024A (More) Realistic Evaluation Setup for Generalisation of Community Models on Malicious Content Detectioncited by 1
  34. 2024Assessing Text Classification Methods for Cyberbullying Detection on Social Media Platformscited by 1
  35. 2025Graphically Speaking: Unmasking Abuse in Social Media with Conversation Insightscited by 1
  36. 2025Culture Matters in Toxic Language Detection in Persiancited by 1
  37. 2023ChatGPT as a commenter to the news: can LLMs generate human-like opinions?cited by 0
  38. 2024HateGPT: Unleashing GPT-3.5 Turbo to Combat Hate Speech on Xcited by 0

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