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Historical forecast errors can be more valuable than target values, as RATL shows significant performance gains in multivariate time-series forecasting by retrieving and utilizing these residuals.
Cross-frame feedback boosts Transformer tracking performance by leveraging historical information, outperforming traditional same-frame methods by up to 3.2 AO points.
