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Two Sample Sizes in Test-Time LLM Ensembling: Buffered ERM and Minimax Theory
Test-time scaling can improve the performance of large language models by generating multiple answers to a question and aggregating them. Weighted ensembles extend this idea by drawing answers from several models, with the weights determining how often each model is used. Learning these weights from
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