Multi-Prompt Aggregation

Drawing on the idea of ensemble learning to reduce variance, this strategy constructs multiple semantically equivalent but differently worded prompts for the same evaluation task, obtains judge verdicts separately, and combines them by voting, averaging, or consistency weighting to improve robustness.