hallucination

Artificial Analysis's broad-knowledge benchmark - thousands of curated factual questions spanning specialized domains - designed to test hallucination calibration.

Stanford CRFM's wide-coverage evaluation framework - dozens of scenarios scored on accuracy, calibration, robustness, fairness, bias, toxicity, and efficiency.

4,326 short factual questions with a single unambiguous answer, designed to measure short-form factuality and calibrate hallucination rate.

817 questions targeting common human misconceptions, measuring whether a model gives factually true answers or repeats popular falsehoods.

Vals.ai's proprietary suite of legal-domain benchmarks (contract review, hallucination tests, LegalBench Pro) used by law firms to procure LLMs.

Anthropic's foundational helpful-and-harmless human preference dataset - the first major public RLHF corpus and a long-time community baseline.

Multi-turn open-web research QA environment where the model uses a Serper search tool to answer hard, hop-heavy questions of the BrowseComp / SimpleQA style.

SimpleQA eval

SimpleQA evaluation environment

SimpleQA-Verified evaluation environment with accuracy scoring.

SimpleQA-Verified evaluation environment with accuracy scoring.

Environment for single-turn tasks in OpenBench