mlsanityData to 7 Oct 2026

HateXplain: A Benchmark Dataset for Explainable Hate Speech Detection

arXiv 2012.10289 ↗First posted 18 Dec 2020cs.CL cs.AI cs.SIcited by 403

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Abstract (arXiv)

Hate speech is a challenging issue plaguing the online social media. While better models for hate speech detection are continuously being developed, there is little research on the bias and interpretability aspects of hate speech. In this paper, we introduce HateXplain, the first benchmark hate speech dataset covering multiple aspects of the issue. Each post in our dataset is annotated from three different perspectives: the basic, commonly used 3-class classification (i.e., hate, offensive or normal), the target community (i.e., the community that has been the victim of hate speech/offensive speech in the post), and the rationales, i.e., the portions of the post on which their labelling decision (as hate, offensive or normal) is based. We utilize existing state-of-the-art models and observe that even models that perform very well in classification do not score high on explainability metrics like model plausibility and faithfulness. We also observe that models, which utilize the human rationales for training, perform better in reducing unintended bias towards target communities. We have made our code and dataset public at https://github.com/punyajoy/HateXplain

Key facts. Cited by 403 papers in the map (data through 7 Oct 2026). First posted on arXiv 18 Dec 2020.

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Citing papers per year: 2021: 28; 2022: 69; 2023: 86; 2024: 87; 2025: 79; 2026: 54.

403 papers.

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  1. 2021MetaICL: Learning to Learn In Contextcited by 450
  2. 2023Explainability for Large Language Models: A Surveycited by 331
  3. 2023From Pretraining Data to Language Models to Downstream Tasks: Tracking the Trails of Political Biases Leading to Unfair NLP Modelscited by 257
  4. 2021Trustworthy AI: From Principles to Practicescited by 206
  5. 2022Delta Tuning: A Comprehensive Study of Parameter Efficient Methods for Pre-trained Language Modelscited by 179
  6. 2021CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLPcited by 142
  7. 2021Teach Me to Explain: A Review of Datasets for Explainable Natural Language Processingcited by 126
  8. 2023A Survey on Fairness in Large Language Modelscited by 91
  9. 2021Human-in-the-Loop for Data Collection: a Multi-Target Counter Narrative Dataset to Fight Online Hate Speechcited by 81
  10. 2022On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representationscited by 75
  11. 2024Risk Taxonomy, Mitigation, and Assessment Benchmarks of Large Language Model Systemscited by 63
  12. 2023HAGRID: A Human-LLM Collaborative Dataset for Generative Information-Seeking with Attributioncited by 55
38 more
  1. 2023Probing LLMs for hate speech detection: strengths and vulnerabilitiescited by 52
  2. 2022Multilingual HateCheck: Functional Tests for Multilingual Hate Speech Detection Modelscited by 51
  3. 2024Machine Unlearning in Generative AI: A Surveycited by 49
  4. 2022Debiasing isn't enough! -- On the Effectiveness of Debiasing MLMs and their Social Biases in Downstream Taskscited by 48
  5. 2022NormSAGE: Multi-Lingual Multi-Cultural Norm Discovery from Conversations On-the-Flycited by 48
  6. 2023SemEval-2023 Task 10: Explainable Detection of Online Sexismcited by 48
  7. 2023"HOT" ChatGPT: The promise of ChatGPT in detecting and discriminating hateful, offensive, and toxic comments on social mediacited by 45
  8. 2023Facilitating Fine-grained Detection of Chinese Toxic Language: Hierarchical Taxonomy, Resources, and Benchmarkscited by 45
  9. 2022GlobEnc: Quantifying Global Token Attribution by Incorporating the Whole Encoder Layer in Transformerscited by 44
  10. 2023Evaluating GPT-3 Generated Explanations for Hateful Content Moderationcited by 44
  11. 2023Exploring Cross-Cultural Differences in English Hate Speech Annotations: From Dataset Construction to Analysiscited by 44
  12. 2025LLMs for Explainable AI: A Comprehensive Surveycited by 42
  13. 2022Human-Machine Collaboration Approaches to Build a Dialogue Dataset for Hate Speech Counteringcited by 40
  14. 2022Large-Scale Hate Speech Detection with Cross-Domain Transfercited by 39
  15. 2021Your fairness may vary: Pretrained language model fairness in toxic text classificationcited by 38
  16. 2023You Only Prompt Once: On the Capabilities of Prompt Learning on Large Language Models to Tackle Toxic Contentcited by 37
  17. 2024FairMT-Bench: Benchmarking Fairness for Multi-turn Dialogue in Conversational LLMscited by 36
  18. 2021Learn Continually, Generalize Rapidly: Lifelong Knowledge Accumulation for Few-shot Learningcited by 35
  19. 2022Toxicity Detection with Generative Prompt-based Inferencecited by 35
  20. 2022Hate Speech and Counter Speech Detection: Conversational Context Does Mattercited by 32
  21. 2023DecompX: Explaining Transformers Decisions by Propagating Token Decompositioncited by 31
  22. 2022Using Pre-Trained Language Models for Producing Counter Narratives Against Hate Speech: a Comparative Studycited by 30
  23. 2023HARE: Explainable Hate Speech Detection with Step-by-Step Reasoningcited by 30
  24. 2024Content Moderation by LLM: From Accuracy to Legitimacycited by 30
  25. 2021Supervising Model Attention with Human Explanations for Robust Natural Language Inferencecited by 29
  26. 2022CounterGeDi: A controllable approach to generate polite, detoxified and emotional counterspeechcited by 28
  27. 2023Robust Hate Speech Detection in Social Media: A Cross-Dataset Empirical Evaluationcited by 28
  28. 2021A systematic review of Hate Speech automatic detection using Natural Language Processingcited by 26
  29. 2022ferret: a Framework for Benchmarking Explainers on Transformerscited by 26
  30. 2024Recent Advances in Hate Speech Moderation: Multimodality and the Role of Large Modelscited by 26
  31. 2021Exploring Universal Intrinsic Task Subspace via Prompt Tuningcited by 25
  32. 2023Zero-Shot Robustification of Zero-Shot Modelscited by 24
  33. 2024"They are uncultured": Unveiling Covert Harms and Social Threats in LLM Generated Conversationscited by 24
  34. 2022Data Bootstrapping Approaches to Improve Low Resource Abusive Language Detection for Indic Languagescited by 23
  35. 2022How Hate Speech Varies by Target Identity: A Computational Analysiscited by 23
  36. 2024From Languages to Geographies: Towards Evaluating Cultural Bias in Hate Speech Datasetscited by 23
  37. 2024Hate Personified: Investigating the role of LLMs in content moderationcited by 23
  38. 2022Perplexed by Quality: A Perplexity-based Method for Adult and Harmful Content Detection in Multilingual Heterogeneous Web Datacited by 22

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