8 citations · 16 across the 5 of their papers we have counts for
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…
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…
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…
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…