Holistic Evaluation of Language Models
by Stanford CRFM · open-source · Last verified 2026-03-17
Presents HELM, a holistic evaluation framework for language models across 42 scenarios and 59 metrics including accuracy, calibration, robustness, fairness, bias, toxicity, and efficiency. HELM reveals that no single model dominates across all dimensions and exposes significant gaps between narrow and comprehensive model assessment.
https://arxiv.org/abs/2211.09110 ↗B+
B+—Good
Adoption: AQuality: A+Freshness: BCitations: AEngagement: F
Specifications
- License
- Apache-2.0
- Pricing
- open-source
- Capabilities
- multi-scenario-evaluation, fairness-assessment, calibration, toxicity-measurement, efficiency-benchmarking
- Integrations
- Use Cases
- model-evaluation, model-comparison, research, responsible-ai
- API Available
- No
- Tags
- evaluation, benchmark, holistic, language-models, multimetric
- Added
- 2026-03-17
- Completeness
- 100%
Index Score
73Adoption
82
Quality
91
Freshness
62
Citations
88
Engagement
0
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