{"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":"bc0095bb-7e88-57de-9936-19ef76832242","task_key":"default--test--10731","task_revision_id":"1","upstream_id":"10731","short_description":"For Kernel Regression, which one of these structural assumptions is the one that…","config":"default","split":"test","body":"{\"category\":\"computer science\",\"options\":\"['The type of regression model used', 'Whether kernel function is Gaussian versus triangular versus box-shaped', 'Whether we use Euclidian versus L1 versus L∞ metrics', 'The distance function used in the kernel', 'The kernel width', 'The number of data points used in the regression', 'The minimum height of the kernel function', 'The dimensionality of the data', 'The maximum height of the kernel function', \\\"The shape of the kernel function's tails\\\"]\",\"question\":\"For Kernel Regression, which one of these structural assumptions is the one that most affects the trade-off between underfitting and overfitting:\",\"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":[]}