AI RESEARCH
ForecastCompass: Guiding Agentic Forecasting with Adaptive Factor Memory
arXiv CS.LG
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ArXi:2605.30858v1 Announce Type: new Agentic forecasting is important for decision-making in dynamic environments, but it remains challenging because agents must reason from incomplete, time-limited evidence and produce calibrated probabilities before outcomes are resolved. Memory provides a natural mechanism for transferring experience from resolved forecasts to future prediction tasks.