RelBench v2 expands a relational deep learning benchmark with four new large datasets and autocomplete tasks, showing models that use table relationships outperform single-table baselines.
Relgnn: Composite message passing for relational deep learning.arXiv preprint arXiv:2502.06784
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RelPrism generates self-supervised pseudo-tasks from three attribute perspectives via multi-granularity clustering to improve representation learning for relational database prediction tasks.
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RelBench v2: A Large-Scale Benchmark and Repository for Relational Data
RelBench v2 expands a relational deep learning benchmark with four new large datasets and autocomplete tasks, showing models that use table relationships outperform single-table baselines.
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RelPrism: A Multi-Faceted Pre-training Framework with Self-Generated Tasks for Relational Databases
RelPrism generates self-supervised pseudo-tasks from three attribute perspectives via multi-granularity clustering to improve representation learning for relational database prediction tasks.
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