{"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":"ca88ef50-2a76-59c5-9707-980e75f741d4","task_key":"all--test--ca88ef50-2a76-59c5-9707-980e75f741d4","task_revision_id":"1","upstream_id":"","short_description":"Statement 1| When learning an HMM for a fixed set of observations, assume we do…","config":"all","split":"test","body":"{\"choices\":\"['True, True', 'False, False', 'True, False', 'False, True']\",\"question\":\"Statement 1| When learning an HMM for a fixed set of observations, assume we do not know the true number of hidden states (which is often the case), we can always increase the training data likelihood by permitting more hidden states. Statement 2| Collaborative filtering is often a useful model for modeling users' movie preference.\",\"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":[]}