Develops ENDS procedure using answer-wise acceptance sets, restricted GLR stopping, and answer-pitfall decomposition for ranking-and-selection with non-unique answers and non-answerable estimates.
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Pith papers citing it
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2026 3representative citing papers
Zero-shot LLM-generated survey data captures broad state-level health contrasts but shows variable-dependent errors that propagate unevenly through IPF-based population synthesis.
A two-step agentic system for extracting insights from VSM simulations achieves up to 86% accuracy with top LLMs by using progressive data discovery and slim context.
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Ranking-and-Selection with Multiple Correct Answers and Non-Answerable Estimates
Develops ENDS procedure using answer-wise acceptance sets, restricted GLR stopping, and answer-pitfall decomposition for ranking-and-selection with non-unique answers and non-answerable estimates.
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Using Zero-Shot LLM-Generated Survey Data for Geographically Explicit Population Synthesis
Zero-shot LLM-generated survey data captures broad state-level health contrasts but shows variable-dependent errors that propagate unevenly through IPF-based population synthesis.
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Agentic Insight Generation in VSM Simulations
A two-step agentic system for extracting insights from VSM simulations achieves up to 86% accuracy with top LLMs by using progressive data discovery and slim context.