implementation detail · filed under evaluation
Prompt engineering to elicit answers
Using prompt engineering to enforce an answer from models that otherwise show refusal behavior.
Also called enforce an answer via prompt engineering.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
For WorldVQA, we observe consistent refusal behavior across models and enforce an answer via prompt engineering.
usedevaluation onlyin WorldVQA evaluationMoonshot AI
Filed alongside
Other methods under evaluation.
Prompt-based output standardizationEvaluation without safety filtersRefusal-suppressed variants for capability estimationavg@kAlmost@1Behavior testing with stubs and edge casesDeadline-bounded rollout evaluationDiverse benchmark validation for quantizationDocumenting evaluation configurationEnd-to-end exploit development evaluationEvaluation equivalence thresholdFixed MTP draft-token acceptance lengthFour-run mean pass@1Full trajectory releaseJoint validation protocolMean@5Model–harness co-designOfficial-release-source baseline restrictionProtocolQA robustness validationRefusal behavior quantificationRollout-based auditingSample test and length-constraint filteringSandboxed GPU kernel optimization evaluationSingle-agent and multi-agent evaluation configurations