Foundation models slightly outperform task-specific models on probabilistic electricity price forecasts but the gap narrows or reverses with extra features or few-shot adaptation, showing that efficiency often outweighs marginal accuracy gains.
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Current proper scoring rules in probabilistic electricity price forecasting prioritize sharpness at the expense of calibration, leading to overconfident and unreliable uncertainty estimates.
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Assessing the Performance-Efficiency Trade-off of Foundation Models in Probabilistic Electricity Price Forecasting
Foundation models slightly outperform task-specific models on probabilistic electricity price forecasts but the gap narrows or reverses with extra features or few-shot adaptation, showing that efficiency often outweighs marginal accuracy gains.
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Investigating Calibration Challenges in Probabilistic Electricity Price Forecasting
Current proper scoring rules in probabilistic electricity price forecasting prioritize sharpness at the expense of calibration, leading to overconfident and unreliable uncertainty estimates.