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POEM's innovative use of $\mathrm{SO}(2)$ rotations reveals how to effectively manage periodicity drift, transforming time series forecasting.
LLMs struggle to match human decision-making in e-commerce, achieving only 27.3% of the final net assets in a year-long simulation.
Weak student agents can learn effectively from their failures through targeted skill patches that bridge the gap between their capabilities and those of stronger teacher models.
