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Holistic Evaluation of Language Models
Holistic Evaluation of Language Models is identified by its primary project source as an evaluation family covering holistic evaluation and scenario coverage. This entry publishes independently authored task signatures only.
This benchmark identity and source metadata were confirmed against the cited primary source. Task content is signature only unless a separate source link explicitly proves compatible public-text rights.
holistic evaluation scenario coverage
Primary source: Stanford CRFM
Source evidence
Tasks
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Evidence integration
Evaluate whether an agent can combine several provided facts without adding unsupported premises in a closed-context reasoning task. Success is determined when the answer is entailed by the provided evidence.
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Calibrated uncertainty
Evaluate whether an agent can identify when available evidence is insufficient for a unique answer in a reasoning task with explicit answer options. Success is determined when the response matches the evaluator's uncertainty condition.
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Inductive reasoning
Evaluate whether an agent can infer a rule from examples and apply it to a new case in a controlled symbolic task. Success is determined when the inferred answer matches the held-out checker.
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Structured reasoning
Evaluate whether an agent can solve a bounded multi-step reasoning problem in a text-only evaluation environment. Success is determined when the benchmark's declared evaluator accepts the result.
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