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DTBench: A Synthetic Benchmark for Document-to-Table Extraction
Yuxiang Guo, Zhuoran Du, Nan Tang +3
Document-to-table (Doc2Table) extraction derives structured tables from unstructured documents under a target schema, enabling reliable and verifiable SQL-based data analytics. Alt…
LASER: A Data-Centric Method for Low-Cost and Efficient SQL Rewriting based on SQL-GRPO
Jiahui Li, Tongwang Wu, Yuren Mao +3
Query rewriting, the process of transforming queries into semantically equivalent yet more efficient variants, is crucial for database optimization. Existing solutions predominantl…
SQL-Factory: A Multi-Agent Framework for High-Quality and Large-Scale SQL Generation
Jiahui Li, Tongwang Wu, Yuren Mao +3
High quality SQL corpus is essential for intelligent database. For example, Text-to-SQL requires SQL queries and correspond natural language questions as training samples. However,…
Birdie: Natural Language-Driven Table Discovery Using Differentiable Search Index
Yuxiang Guo, Zhonghao Hu, Yuren Mao +3
Natural language (NL)-driven table discovery identifies relevant tables from large table repositories based on NL queries. While current deep-learning-based methods using the tradi…
DAgent: A Relational Database-Driven Data Analysis Report Generation Agent
Wenyi Xu, Yuren Mao, Xiaolu Zhang +4
Relational database-driven data analysis (RDB-DA) report generation, which aims to generate data analysis reports after querying relational databases, has been widely applied in fi…
Snoopy: Effective and Efficient Semantic Join Discovery via Proxy Columns
Yuxiang Guo, Yuren Mao, Zhonghao Hu +2
Semantic join discovery, which aims to find columns in a table repository with high semantic joinabilities to a query column, is crucial for dataset discovery. Existing methods can…