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This paper introduces EGGROLL, a method using low-rank Gaussian perturbations to make evolution strategies practical for large language models, and proposes LOO-ROLL, an improved leave-one-out estimator that enhances performance and reduces variance, with significant accuracy gains on the GSM8K benchmark.