dailyai.report

Targeted filtering of training data often fails to eliminate specific model behaviors like liberal lean or bold formatting. Researchers using OLMo found that removing problematic data points during supervised fine-tuning had little effect on the final output. This suggests that simple data curation cannot reliably scrub undesirable traits from LLMs.