Unverified50% confidenceFactExact time
METR's methodology requires evaluators to be able to call the model directly, design controlled experiments, and observe the model's performance on unseen tasks.
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10/17/2026
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UnverifiedBuilding one's own evaluations can turn model selection into a data-driven decision, using one's own evaluation set to run real-task performance data to determine whether to switch models.75% similarUnverifiedBy keeping the scene constant and only replacing the key object in controlled comparative experiments, the model's physical reasoning capabilities can be observed under controlled conditions.75% similarUnverifiedEmbodied evaluation is having a model complete tasks in a simulated or real physical environment, involving action sequence planning, changes in environmental state, and causal inference, where the correctness of the task depends on the final environmental state rather than intermediate answers.74% similarUnverifiedSelf-reflection is achieved by having the model evaluate the quality of its own output and iteratively improve it; the Reflexion framework demonstrates that an agent can learn from failed attempts and adjust its strategy in the next iteration.74% similar
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