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@@ -34,4 +34,36 @@ configs:
     path: "test/mmlu_YO-NG.csv"
   - split: ZH_CN
     path: "test/mmlu_ZH-CN.csv"
----
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+---
+
+# Multilingual Massive Multitask Language Understanding (MMMLU)
+
+The MMLU is a widely recognized benchmark of general knowledge attained by AI models. It covers a broad range of topics from 57 different categories, covering elementary-level knowledge up to advanced professional subjects like law, physics, history, and computer science.
+
+We translated the MMLU’s test set into 14 languages using professional human translators. Relying on human translators for this evaluation increases confidence in the accuracy of the translations, especially for low-resource languages like Yoruba. We are publishing the professional human translations and the code we use to run the evaluations.
+
+This effort reflects our commitment to improving the multilingual capabilities of AI models, ensuring they perform accurately across languages, particularly for underrepresented communities. By prioritizing high-quality translations, we aim to make AI technology more inclusive and effective for users worldwide.
+
+## Locales
+
+MMMLU contains the MMLU test set translated into the following locales:
+* AR_XY (Arabic)
+* BN_BD (Bengali)
+* DE_DE (German)
+* ES_LA (Spanish)
+* FR_FR (French)
+* HI_IN (Hindi)
+* ID_ID (Indonesian)
+* IT_IT (Italian)
+* JA_JP (Japanese)
+* KO_KR (Korean)
+* PT_BR (Brazilian Portuguese)
+* SW_KE (Swahili)
+* YO_NG (Yoruba)
+* ZH_CH (Simplied Chinese)
+
+## Sources
+
+Hendrycks, D., Burns, C., Kadavath, S., Arora, A., Basart, S., Tang, E., Song, D., & Steinhardt, J. (2021). [*Measuring Massive Multitask Language Understanding*](https://arxiv.org/abs/2009.03300).
+
+[OpenAI Simple Evals GitHub Repository](https://github.com/openai/simple-evals)
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