dailyai.report

Targeted filtering of training data often fails to eliminate specific model behaviors like liberal-leaning responses or bold formatting. Researchers using OLMo SFT datasets found that removing problematic data points had little effect on the final model output. This suggests that standard data attribution methods are insufficient for precise behavioral control during fine-tuning.