{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"mmlu-pro","formal_name":"MMLU-Pro","introduction":"MMLU-Pro rebuilds MMLU with ten answer options instead of four and removes items that no longer separate models. Questions span fourteen academic and professional subjects.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro","indexing_mode":"index","profile":{"resources":[],"task_format":"","scoring":"","metric":"","size":"","answer_access":"","license":"","citation":"","maintainer":"","released":"","why_hard":"","related":[],"history":"","construction":"","limitations":"","saturation":"","scores":[]}},"task_id":"d0dd2699-b123-5d30-b7d2-d97d90d34e75","task_key":"default--test--10494","task_revision_id":"1","upstream_id":"10494","short_description":"Which of the following is false?","config":"default","split":"test","body":"{\"category\":\"computer science\",\"options\":\"['The loss $\\\\\\\\log \\\\\\\\sigma(x)= -\\\\\\\\log(1+e^{-x})$ is concave', 'Leaky ReLU $\\\\\\\\max\\\\\\\\{0.01x,x\\\\\\\\}$ is convex.', 'The following fully connected network without activation functions is linear: $g_3(g_2(g_1(x)))$, where $g_i(x) = W_i x$ and $W_i$ are matrices.', 'A combination of ReLUs such as $ReLU(x) - ReLU(x-1)$ is convex.']\",\"question\":\"Which of the following is false?\",\"src\":\"ori_mmlu-machine_learning\"}","display_format":"text","language":"","answer_status":"published","assets":[],"source_url":"https://huggingface.co/datasets/TIGER-Lab/MMLU-Pro","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}