MM-Eval

Large language models (LLMs) excel in high-resource languages but face notable challenges in low-resource languages like Mongolian. The release of MM-Eval, comprising 569 syntax, 677 semantics, 344 knowledge, and 250 reasoning tasks, offers valuable insights for advancing NLP and LLMs in low-resource languages like Mongolian.