{"url":"/dataset/helm","name":"HELM","full_name":"Holistic Evaluation of Language Models","description_markdown":"The Holistic Evaluation of Language Models (HELM) is a comprehensive framework developed by Stanford University for evaluating foundation language models. It serves as a living benchmark, promoting transparency in language models. Here are the key aspects of HELM:\r\n\r\nPurpose: HELM aims to provide a holistic view of language models by considering various dimensions and metrics.\r\nCoverage: It encompasses a wide range of scenarios and recognizes the inherent incompleteness of existing models.\r\nMetrics: HELM employs multiple metrics to assess language models.\r\nStandardization: The framework promotes standardization in evaluation practices.\r\nAccessibility: All data and analyses are freely accessible on the HELM website for exploration and study.","description_withheld":null,"homepage":"https://crfm.stanford.edu/helm/classic/latest","introduced_date":"2022-11-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/holistic-evaluation-of-language-models","title":"Holistic Evaluation of Language Models","first_author":"Percy Liang","url":null},"license":null,"modalities":[],"tasks":[],"languages":[],"variants":["HELM"],"data_loaders":[],"num_papers_in_archive":165,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}