EcoTable is the first NL-based data integration framework that builds a join-likelihood graph, uses two-stage schema linking and Steiner tree search to find paths, then generates transformations with LLMs, reporting >30% accuracy gain and 5x lower cost on four real-world datasets.
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3 Pith papers cite this work. Polarity classification is still indexing.
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Develops TWSF estimator for causal forecasting in panel data by combining synthetic controls with time-series models under low-rank latent factor assumptions, providing finite-sample bounds and asymptotic normality.
A survey of LLMs for graph computation introduces a role-based taxonomy of executors versus planners and concludes that current models suit simple small-scale tasks but remain unreliable for large-scale exact computation.
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Are Large Language Models Suitable for Graph Computation? Progress and Prospects
A survey of LLMs for graph computation introduces a role-based taxonomy of executors versus planners and concludes that current models suit simple small-scale tasks but remain unreliable for large-scale exact computation.