Humanity's Last Exam

Eli Meril

Abstract:

Benchmarks are important tools for tracking the rapid advancements in large language model (LLM) capabilities. However, benchmarks are not keeping pace in
difficulty: LLMs now achieve over 90% accuracy on popular benchmarks like
MMLU, limiting informed measurement of state-of-the-art LLM capabilities. In
response, we introduce HUMANITY’S LAST EXAM (HLE), a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended
academic benchmark of its kind with broad subject coverage. HLE consists of
2,500 questions across dozens of subjects, including mathematics, humanities, and
the natural sciences. HLE is developed globally by subject-matter experts and consists of multiple-choice and short-answer questions suitable for automated grading.
Each question has a known solution that is unambiguous and easily verifiable, but
cannot be quickly answered via internet retrieval. State-of-the-art LLMs demonstrate low accuracy and calibration on HLE, highlighting a significant gap between
current LLM capabilities and the expert human frontier on closed-ended academic
questions. To inform research and policymaking upon a clear understanding of
model capabilities, we publicly release HLE at https://lastexam.ai.