Research
AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African Languages vs IrokoBench: A New Benchmark for African Languages in the Age of Large Language Models
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AfriHate: A Multilingual Collection of Hate Speech and Abusive Language Datasets for African LanguagesIrokoBench: A New Benchmark for African Languages in the Age of Large Language Models
Category
Research
Research
Type
NLP benchmark
NLP benchmark
Country
🌍 Pan-African
🌍 Pan-African
Docs status
Docs live
Docs live
Licensing
Pricing
Free / open
Free / open
Verified
Unverified
Unverified
Last verified
5 Jul 2026
5 Jul 2026
Tags
african-languages, hate-speech, nlp-benchmark, content-moderation
african-languages, masakhane, nlp-benchmark, llm-evaluation
Summary
AfriHate is a multilingual benchmark of hate speech and abusive language datasets covering 15 African languages, annotated by native speakers. The paper contributes classification baselines and hate speech and offensive language lexicons, and analyses why keyword-based moderation fails for low-resource African languages. It was released on arXiv in January 2025.
IrokoBench is a human-translated evaluation benchmark covering 17 typologically diverse low-resource African languages across three tasks: natural language inference (AfriXNLI), mathematical reasoning (AfriMGSM) and knowledge-based multiple-choice QA (AfriMMLU). The paper evaluates open and proprietary LLMs and documents a large gap between high-resource languages and African languages, with the best open model reaching about 63 percent of GPT-4o performance. It was published at NAACL 2025.