BLS approximates per-sample loss importance via EMA of batch losses, enabling simple and effective dynamic pruning of 20-50% samples losslessly across many datasets and models.
This line, within the training loop, calls the update method
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Batch Loss Score for Dynamic Data Pruning
BLS approximates per-sample loss importance via EMA of batch losses, enabling simple and effective dynamic pruning of 20-50% samples losslessly across many datasets and models.