4 papers · 1 filter
Forecasting Supply Chain Disruptions with Foresight Learning
Benjamin Turtel, Paul Wilczewski, Kris Skotheim
Anticipating supply chain disruptions before they materialize is a core challenge for firms and policymakers alike. A key difficulty is learning to reason reliably about infrequent…
Foresight Learning for SEC Risk Prediction
Benjamin Turtel, Paul Wilczewski, Danny Franklin +1
Risk disclosures in SEC filings describe potential adverse events but rarely quantify their likelihood, limiting their usefulness for probabilistic analysis. A central obstacle is…
Future-as-Label: Scalable Supervision from Real-World Outcomes
Benjamin Turtel, Paul Wilczewski, Danny Franklin +1
Time creates free supervision: forecasts about real-world events resolve to verifiable outcomes. The passage of time provides labels that require no annotation. To exploit this str…
Outcome-based Reinforcement Learning to Predict the Future
Benjamin Turtel, Danny Franklin, Kris Skotheim +2
Reinforcement Learning with Verifiable Rewards (RLVR) has been an effective approach for improving Large Language Models' reasoning in domains such as coding and mathematics. Here,…