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New PlanPool method improves agentic Text-to-SQL systems

By PulseAugur Editorial · [1 sources] ·

Researchers have developed a new method called PlanPool to address underspecification in agentic Text-to-SQL systems. These systems can interact with users to clarify ambiguous queries, but they sometimes make unverified assumptions that lead to correct execution results without fully resolving the ambiguity. PlanPool externalizes the clarification plan as a mutable question pool, ensuring that all identified relevant questions are explicitly asked or dropped before an answer is submitted. This approach improves ambiguity coverage and reduces silent failures across multiple benchmarks while maintaining competitive execution accuracy. AI

IMPACT Enhances the reliability of AI systems that translate natural language to database queries by ensuring thorough clarification of user intent.

RANK_REASON Academic paper introducing a new method for agentic Text-to-SQL systems. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New PlanPool method improves agentic Text-to-SQL systems

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Academic paper introducing a new method for agentic Text-to-SQL systems. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Wen-Zhi Li, Yue Gong, Konstantinos Kanellis, Balakrishnan Murali Narayanaswamy ·

    Beyond Correctness: Resolving Underspecification in Agentic Text-to-SQL

    arXiv:2610.02739v1 Announce Type: new Abstract: Agentic Text-to-SQL systems can interact with users to clarify underspecified queries before generating SQL. However, a correct execution result does not necessarily imply that the agent has adequately resolved the underlying unders…

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