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This study proposes the TAISE framework, which repurposes AI weather forecasting models to produce coherent extreme weather sequences at a fraction of traditional costs, and suggests a pathway toward democratising catastrophe risk quantification and enabling dynamic, comprehensive portfolio assessment for insurers, reinsurers, ILS fund managers and public-sector risk managers.
Temporal GRPO reveals that aligning reinforcement learning updates with task stages can significantly boost both efficiency and success rates in complex vision-language-action tasks.
