EstGraph benchmark evaluates LLMs on estimating properties of very large graphs from random-walk samples that fit in context limits.
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2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
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cs.LG 2years
2026 2verdicts
UNVERDICTED 2representative citing papers
Long-Term Embeddings anchor sequential recommendation models to fixed content-based item representations to capture stable preferences and ensure version compatibility, resulting in uplifts in user engagement and financial metrics.
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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Long-Term Embeddings for Balanced Personalization
Long-Term Embeddings anchor sequential recommendation models to fixed content-based item representations to capture stable preferences and ensure version compatibility, resulting in uplifts in user engagement and financial metrics.