dailyai.report

Seven hypotheses explain why filtering supervised fine-tuning data fails to remove undesirable model traits. Google DeepMind researchers identified hereditary flaws in Gemini, including negative emotion and date confusion. These persistent behaviors resist simple data scrubbing. Practitioners must look beyond basic SFT filters to ensure robust model alignment and safety.