GenTUS reformulates table union search as constrained generative retrieval over semantic table identifiers, achieving top retrieval quality on seven benchmarks with lower latency and storage costs.
In: The World Wide Web Conference
4 Pith papers cite this work, alongside 281 external citations. Polarity classification is still indexing.
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Pith papers citing it
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Unconstrained LLM rewriting of RDF dataset metadata maximizes retrieval gains but is least faithful; profile-grounded rewriting best balances effectiveness and grounding.
Structured schema.org metadata still gives dataset-retrieval agents a large precision advantage for machine-actionable data.
PIPER retrieves and ranks tabular datasets by profiling their content and using LLM-generated queries for dense vector search, outperforming metadata baselines and TableQA methods in low-metadata settings.
citing papers explorer
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Generative Retrieval for Table Union Search
GenTUS reformulates table union search as constrained generative retrieval over semantic table identifiers, achieving top retrieval quality on seven benchmarks with lower latency and storage costs.
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Faithful or Findable? Evaluating LLM-Generated Metadata for RDF Dataset Search
Unconstrained LLM rewriting of RDF dataset metadata maximizes retrieval gains but is least faithful; profile-grounded rewriting best balances effectiveness and grounding.
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Do Data Agents Need Semantic Metadata? A Comparative Study in Agentic Data Retrieval
Structured schema.org metadata still gives dataset-retrieval agents a large precision advantage for machine-actionable data.
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PIPER: Content-Based Table Search via profiling and LLM-Generated Pseudoqueries
PIPER retrieves and ranks tabular datasets by profiling their content and using LLM-generated queries for dense vector search, outperforming metadata baselines and TableQA methods in low-metadata settings.