· International Conference on Extending Database Technology· pp. 14-26· 0 citations· 47 references
Computer Science
TL;DR
TABERTA is presented, a unified retrieval framework for dataset discovery that adapts a bi-encoder language model to relational data by fine-tuning it on serialized representations of tables by fine-tuning the language encoder to diverse structural patterns using optimized strategies that serialize schema and table content.
Non-relational tables, such as spreadsheets and web tables, are widely used to store structured data, yet they are primarily designed for human reading rather than machine-driven analysis. These tables often contain hierarchical headers, merged cells, and implicit spatial semantics, making it difficult for large langua...
Li-Nan Zheng, Chuan Lei, Lei Cao· Proceedings of the ACM on Ma...· 0 citations
This work proposes MDB-Link, a hierarchical schema-linking framework that retrieves question-relevant columns from a global index, aggregates retrieval evidence to shortlist databases, and uses a budget-aware large language model (LLM) for database reranking, table selection, and column grounding.
Beiyu Xu, Zhenyu Wu, Jiao-Yan Chen et al.· 0 citations
This study explores a semantic variation methodology to augment training data by generating question-answer pairs with explicit control over semantic similarity, and shows that semantically controlled augmentation improves domain-specific knowledge acquisition while preserving consistency.
Alexander Chen, Caroline Tang, Jennifer Sleeman· TEXT2KG/BiKE@ESWC· 0 citations
Comprehensive evaluations on real-world benchmarks demonstrate that LOKI consistently outperforms state-of-the-art multi-modal data discovery approaches, and materializes typed integrated tables with 0.982 macro typed-pair precision while being up to 40 times cheaper in LLM API cost than direct prompting.
To overcome scarce labeled data, Matryoshka Representation Learning truncation to 256 dimensions preserves 99.9% of retrieval quality while reducing dense-index storage and exact similarity arithmetic by a factor of three.
Konstantin Chesnokov, Chingiz Mingazov· 0 citations
Retrieving the right tables is a prerequisite for Text-to-SQL over realistic databases. Dense table retrievers rank schema elements independently, but this ignores a key source of evidence: some required tables are not mentioned in the question and become identifiable only through their join relationships to already re...
S. De, Abhijit Chakraborty, Sambaran Bandyopadhyay et al.· 0 citations
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