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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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 2verdicts
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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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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.