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The linked article is about a statistical approach to evaluating large language models (LLMs). It discusses the challenges of assessing LLM performance and proposes a framework that combines human evaluations, automated metrics, and statistical modeling to provide a more comprehensive and reliable assessment. The article highlights the importance of considering the uncertainty and variability inherent in LLM evaluations and advocates for a shift towards a statistical approach that can better capture the nuances and limitations of these models.