EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
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3 Pith papers cite this work. Polarity classification is still indexing.
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NPC quantifies egonet persistence in temporal networks via similarity measures and topology-controlled null models, revealing an exploration-exploitation trade-off in conference face-to-face data with weak demographic links.
d-MinIntSep is NP-hard and inapproximable to within a logarithmic factor; an ILP formulation computes minimum interval separators and is tested on synthetic and real transportation temporal networks.
citing papers explorer
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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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Extracting behavioural properties from face-to-face interactions temporal networks: a measure of egonet persistency
NPC quantifies egonet persistence in temporal networks via similarity measures and topology-controlled null models, revealing an exploration-exploitation trade-off in conference face-to-face data with weak demographic links.
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Testing Robustness of Temporal Transportation Networks via Interval Separators
d-MinIntSep is NP-hard and inapproximable to within a logarithmic factor; an ILP formulation computes minimum interval separators and is tested on synthetic and real transportation temporal networks.