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Hendrycks and colleagues: massive multitask language understanding benchmark

Contribution grade

General AI knowledge evaluation · Evaluation resource design

Reference score135,000Provisional editorial estimate of this exact contribution; its grade is assessed separately.

What changed

Introduced a broad subject-based multiple-choice test for evaluating pretrained language models and identifying uneven performance and calibration.

Scientific scope

Introduced a broad subject-based multiple-choice test for evaluating pretrained language models and identifying uneven performance and calibration. Year follows the 2020 preprint. The benchmark is a test collection, not a measure of general intelligence or validated professional competence; later MMLU variants are separate.

Evidence

The linked original sources describe the stated contribution and its evidence limits. WRS has not independently rerun the experiments or certified a proof. Year follows the 2020 preprint. The benchmark is a test collection, not a measure of general intelligence or validated professional competence; later MMLU variants are separate.

Contributors

Provisional WRS assessment, edition 2026-10-16.1. Independent expert calibration is pending. This grade does not certify correctness or assign ownership.

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