When Should Forecasting Agents Reason? Behavioral Stress Tests for Reliability Routing
Establishing a rigorous framework for trust in automated forecasting and decision-support systems.
Forecasting agents increasingly combine language-model reasoning, retrieval, ensembling, and calibration, but it remains unclear when each behavior should be trusted. We study this question on ForecastBench-style binary forecasting tasks, treating the choice to retrieve, reason, ...
ArXiv CS.AI
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This research provides a critical framework for determining when automated systems should rely on internal reasoning versus external data retrieval in high-stakes forecasting. By establishing behavioral stress tests, it offers a path toward more reliable and accountable decision-making models in dynamic environments.
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