mlsanityData to 13 Oct 2026

HateCOT: An Explanation-Enhanced Dataset for Generalizable Offensive Speech Detection via Large Language Models

arXiv 2403.11456 ↗First posted 18 Mar 2024cs.CL cs.AI cs.SIcited by 4

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Abstract (arXiv)

The widespread use of social media necessitates reliable and efficient detection of offensive content to mitigate harmful effects. Although sophisticated models perform well on individual datasets, they often fail to generalize due to varying definitions and labeling of "offensive content." In this paper, we introduce HateCOT, an English dataset with over 52,000 samples from diverse sources, featuring explanations generated by GPT-3.5Turbo and curated by humans. We demonstrate that pretraining on HateCOT significantly enhances the performance of open-source Large Language Models on three benchmark datasets for offensive content detection in both zero-shot and few-shot settings, despite differences in domain and task. Additionally, HateCOT facilitates effective K-shot fine-tuning of LLMs with limited data and improves the quality of their explanations, as confirmed by our human evaluation.

Key facts. Cited by 4 papers in the map (data through 13 Oct 2026). Builds on 44 of its 76 references that are in the map. First posted on arXiv 18 Mar 2024.

Builds on

44 of 76 references.

References · 44

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32 more
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  12. 2020HateCheck: Functional Tests for Hate Speech Detection Modelscited by 216
  13. 2021Latent Hatred: A Benchmark for Understanding Implicit Hate Speechcited by 216
  14. 2020HateBERT: Retraining BERT for Abusive Language Detection in Englishcited by 206
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Cited by year (2026 to 13 Oct)

Citing papers per year: 2024: 1; 2025: 2; 2026: 1.

4 papers.

  1. 2024Content Moderation by LLM: From Accuracy to Legitimacycited by 30
  2. 2025Black Box Absorption: LLMs Undermining Innovative Ideascited by 1
  3. 2025SMARTER: A Data-efficient Framework to Improve Toxicity Detection with Explanation via Self-augmenting Large Language Modelscited by 0
  4. 2026CHAIRO: Contextual Hierarchical Analogical Induction and Reasoning Optimization for LLMscited by 0