Typically unobservable elements
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Second, a reward curriculum via . Between epochs, the parameter in the reward is annealed from recall-focused, weighting recall 16x more than precision toward weighting recall 4x more. Early in training, the recall bias encourages broad exploration: the model is rewarded for finding relevant documents regardless of how much noise it accumulates. As training progresses and the model becomes competent at searching and pruning, is shifted toward precision, encouraging the model to be more selective in what it retains in its final output.
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