A new structured prompting method (SPEC) helps AI detect insufficient evidence in adjudication tasks and defer decisions appropriately, reaching 89% accuracy on a benchmark varying information completeness from Colorado unemployment insurance cases.
Young, Johannes Himmelreich, Danylo Honcharov, and Sucheta Soundarajan
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GRAFT improves electric load forecasting accuracy by aligning multi-source daily texts with half-hour load series and using cross-attention fusion, outperforming baselines on a new Australian benchmark across hourly to monthly horizons.
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Learning When Not to Decide: A Framework for Overcoming Factual Presumptuousness in AI Adjudication
A new structured prompting method (SPEC) helps AI detect insufficient evidence in adjudication tasks and defer decisions appropriately, reaching 89% accuracy on a benchmark varying information completeness from Colorado unemployment insurance cases.
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GRAFT: Grid-Aware Load Forecasting with Multi-Source Textual Alignment and Fusion
GRAFT improves electric load forecasting accuracy by aligning multi-source daily texts with half-hour load series and using cross-attention fusion, outperforming baselines on a new Australian benchmark across hourly to monthly horizons.