SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)

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Cited by

408 papers of our library cite it (of the 140673 whose bibliographies we read); 13 of them have a page here, 395 not yet.

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• Llama Guard: LLM-based Input-Output Safeguard for Human-AI Conversations
• HeBERT & HebEMO: a Hebrew BERT Model and a Tool for Polarity Analysis and Emotion Recognition
• Offensive Hebrew Corpus and Detection using BERT
• Offensive language detection in Hebrew: can other languages help?
• ParaDetox: Detoxification with Parallel Data
• Predicting the Type and Target of Offensive Posts in Social Media
• Sentiment Analysis in the Era of Large Language Models: A Reality Check

Cite

The paper itself, not this page. BibTeX from the library's record of the work. DOI 10.48550/arxiv.1903.08983 · arXiv 1903.08983

@misc{zampieri2019semeval,
  title = {{SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)}},
  author = {Zampieri, Marcos and Malmasi, Shervin and Nakov, Preslav and Rosenthal, Sara and Farra, Noura and Kumar, Ritesh},
  year = {2019},
  doi = {10.48550/arxiv.1903.08983},
  eprint = {1903.08983},
  archivePrefix = {arXiv},
  url = {https://doi.org/10.48550/arxiv.1903.08983}
}

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