EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
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New theoretical results on estimators and intervals for predicting unseen outcomes in additional samples from discrete distributions, with extensions to grouped incidence data.
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Evaluating LLMs on Large-Scale Graph Property Estimation via Random Walks
EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
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The Unseen Species Problem Revisited
New theoretical results on estimators and intervals for predicting unseen outcomes in additional samples from discrete distributions, with extensions to grouped incidence data.