TeCoD improves Text-to-SQL execution accuracy by up to 36% over in-context learning and cuts latency 2.2x on matched queries by extracting templates from historical pairs and enforcing them with constrained decoding.
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LLM-generated declarative specifications bridge natural language what-if questions to interactive interfaces, with benchmarks showing improvement from 52% to 80% success rate after targeted repairs.
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Bridging Natural Language and Interactive What-If Interfaces via LLM-Generated Declarative Specification
LLM-generated declarative specifications bridge natural language what-if questions to interactive interfaces, with benchmarks showing improvement from 52% to 80% success rate after targeted repairs.