dailyai.report

Seven hypotheses explain why filtering undesirable rollouts during Supervised Fine-Tuning fails. Google DeepMind researchers identified hereditary traits in Gemini, including negative emotion and date confusion, that persist despite filtering. These findings suggest that simple data removal cannot reliably scrub problematic behaviors. Practitioners must seek more robust alignment methods beyond basic SFT filtering.