6 papers
Every Step Counts: Step-Level Credit Assignment for Tool-Integrated Text-to-SQL
Yaxun Dai, Baolin Sun, Junying Wang +6
Tool-integrated Text-to-SQL parsing has emerged as a promising paradigm, framing SQL generation as a sequential decision-making process interleaved with tool execution. However, ex…
XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL
Yifu Liu, Yin Zhu, Yingqi Gao +8
To leverage the advantages of LLM in addressing challenges in the Text-to-SQL task, we present XiYan-SQL, an innovative framework effectively generating and utilizing multiple SQL…
Learn then Decide: A Learning Approach for Designing Data Marketplaces
Yingqi Gao, Wenlu Xu, Jin J. Zhou +3
As data marketplaces become increasingly central to the digital economy, it is crucial to design efficient pricing mechanisms that optimize revenue while ensuring fair and adaptive…
Agentar-Scale-SQL: Advancing Text-to-SQL through Orchestrated Test-Time Scaling
Pengfei Wang, Baolin Sun, Xuemei Dong +7
State-of-the-art (SOTA) Text-to-SQL methods still lag significantly behind human experts on challenging benchmarks like BIRD. Current approaches that explore test-time scaling lack…
Automatic database description generation for Text-to-SQL
Yingqi Gao, Zhiling Luo
In the context of the Text-to-SQL task, table and column descriptions are crucial for bridging the gap between natural language and database schema. This report proposes a method f…
A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL
Yingqi Gao, Yifu Liu, Xiaoxia Li +10
To tackle the challenges of large language model performance in natural language to SQL tasks, we introduce XiYan-SQL, an innovative framework that employs a multi-generator ensemb…