9 papers
SAGE: A Unified Algebra and Self-Adaptive Execution for AI Functions in SQL
Xiangqi Wang, Nhan H. Pham, Oktie Hassanzadeh +2
SQL systems increasingly expose AI functions for tasks such as classification, extraction, filtering, ranking, retrieval, joining, and summarization. Despite their diverse APIs, th…
Test-Time Verification for Text-to-SQL via Outcome Reward Models
Mattia Tritto, Giuseppe Farano, Dario Di Palma +4
Improving the reliability of large language models (LLMs) at inference time is a central challenge in structured reasoning tasks such as Text-to-SQL. Common test-time inference str…
Discovery Agents for Real-Time Analytics: Toward Proactive Insight Systems
Gaetano Rossiello, Dharmashankar Subramanian
Modern analytics systems are fundamentally reactive, requiring users to define queries over increasingly complex and continuously evolving data. In real-time streaming environments…
ConstrainedSQL: Training LLMs for Text2SQL via Constrained Reinforcement Learning
Weiqin Chen, Nhan Huu Pham, Michael Robert Glass +4
Reinforcement learning (RL) has demonstrated significant promise in enhancing the reasoning capabilities of Text2SQL LLMs, especially with advanced algorithms such as GRPO and DAPO…
GradeSQL: Test-Time Inference with Outcome Reward Models for Text-to-SQL Generation from Large Language Models
Mattia Tritto, Giuseppe Farano, Dario Di Palma +4
Text-to-SQL, the task of translating natural language questions into SQL queries, has significantly advanced with the introduction of Large Language Models (LLMs), broadening datab…
Knowledge Base Construction for Knowledge-Augmented Text-to-SQL
Jinheon Baek, Horst Samulowitz, Oktie Hassanzadeh +4
Text-to-SQL aims to translate natural language queries into SQL statements, which is practical as it enables anyone to easily retrieve the desired information from databases. Recen…