Datasets › HELM
HELM (Holistic Evaluation of Language Models)
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:
Purpose: HELM aims to provide a holistic view of language models by considering various dimensions and metrics. Coverage: It encompasses a wide range of scenarios and recognizes the inherent incompleteness of existing models. Metrics: HELM employs multiple metrics to assess language models. Standardization: The framework promotes standardization in evaluation practices. Accessibility: All data and analyses are freely accessible on the HELM website for exploration and study.
Benchmarks archive 2025-07-28
No leaderboard in the archive resolves to this dataset.
Papers archive 2025-07-28
No paper in the archive has a leaderboard row on this dataset; the archive counts 165 papers for it but never published that list.
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
No task tagged in the archive.
License archive 2025-07-28
No licence recorded in the archive. Absence here is not a statement about the dataset's terms.
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- HELM
1 variant name, as the archive lists them.
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