EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
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Institutional delays trigger instability in multi-agent systems through delayed repression, with simulations identifying reactivity to lagged signals as the destabilizing factor rather than learning.
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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.