Residual skill optimization creates complementary Text-to-SQL agents by training each new skill on prior ensemble failures, yielding accuracy gains on Spider2-Lite and transfer to other dialects and tasks.
Can llm already serve as a database interface? a big bench for large-scale database grounded text-to-sqls.Advances in Neural Information Processing Systems, 36, 2024
3 Pith papers cite this work. Polarity classification is still indexing.
3
Pith papers citing it
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RUBICON replaces opaque LLM-based tool orchestration in agentic AI with an explicit query algebra (AQL: Find, From, Where) executed via wrappers to deliver traceable, deterministic access to heterogeneous enterprise data systems.
M3 uses LLMs to translate natural language into SQL for the MIMIC-IV database, achieving 93-94% accuracy on benchmark questions with support for local privacy-preserving deployment.
citing papers explorer
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Residual Skill Optimization for Text-to-SQL Ensembles
Residual skill optimization creates complementary Text-to-SQL agents by training each new skill on prior ensemble failures, yielding accuracy gains on Spider2-Lite and transfer to other dialects and tasks.
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An Alternate Agentic AI Architecture (It's About the Data)
RUBICON replaces opaque LLM-based tool orchestration in agentic AI with an explicit query algebra (AQL: Find, From, Where) executed via wrappers to deliver traceable, deterministic access to heterogeneous enterprise data systems.
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M3: Conversational LLMs Simplify Secure Clinical Data Access, Understanding, and Analysis
M3 uses LLMs to translate natural language into SQL for the MIMIC-IV database, achieving 93-94% accuracy on benchmark questions with support for local privacy-preserving deployment.