{"kind":"task","effective_mode":"full","benchmark":{"kind":"benchmark","effective_mode":"full","slug":"mmlu","formal_name":"MMLU","introduction":"MMLU asks four-way multiple-choice questions across 57 subjects, from elementary material to professional-level examinations. Since 2020 it has been the most widely cited single reference point for general capability.","introduction_ja":"","introduction_en":"","category":"Category not supplied","task_count":null,"acquisition_status":"Acquisition status not supplied","official_url":"https://github.com/hendrycks/test","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":"9056efbe-2397-5630-9105-e3fd22543b29","task_key":"all--test--9056efbe-2397-5630-9105-e3fd22543b29","task_revision_id":"1","upstream_id":"","short_description":"For Kernel Regression, which one of these structural assumptions is the one that…","config":"all","split":"test","body":"{\"choices\":\"['Whether kernel function is Gaussian versus triangular versus box-shaped', 'Whether we use Euclidian versus L1 versus L∞ metrics', 'The kernel width', 'The maximum height of the kernel function']\",\"question\":\"For Kernel Regression, which one of these structural assumptions is the one that most affects the trade-off between underfitting and overfitting:\",\"subject\":\"machine_learning\"}","display_format":"text","language":"","answer_status":"published","assets":[],"source_url":"https://github.com/hendrycks/test","history":"initial import","indexing_mode":"index","subproblems":[],"grids":[]}