arXiv Artificial Intelligence

DualSQL: Text-to-SQL with Multi-Agent Reinforcement Learning

2 hours ago 17.09.2026 07:00 👁 2 views
DualSQL: Text-to-SQL with Multi-Agent Reinforcement Learning

Quick summary

arXiv:2609.18135v1 Announce Type: cross Abstract: State-of-the-art Text-to-SQL systems are typically multi-agent pipelines centered around two fundamental tasks: schema linking and SQL generation. However, existing work trains separate models for each task, failing to leverage the synergy between these interrelated tasks. In this work, we propose DualSQL, a new Text-to-SQL system consisting of two agents powered by a single model backbone. The agents share the same model weights and agentic scaffold, enabling joint optimization through a robust multi-agent reinforcement learning (RL) framework

Key takeaways

  • arXiv:2609.18135v1 Announce Type: cross Abstract: State-of-the-art Text-to-SQL systems are typically multi-agent pipelines centered around two fundamental tasks: schema linking and SQL generation.
  • However, existing work trains separate models for each task, failing to leverage the synergy between these interrelated tasks.
  • In this work, we propose DualSQL, a new Text-to-SQL system consisting of two agents powered by a single model backbone.

Why it matters

This model development creates a new option for users and a new testing obligation for developers. A fixed evaluation set comparing quality, cost and failure behavior is more useful than launch claims.

Kaynak sitede devamını oku: arXiv Artificial Intelligence ↗