DART : Mitigating Harm Drift in Difference-Aware LLM s via Distill-Audit-Repair Training
Ziwen Pan · Zihan Liang · Jad Kabbara · Ali Emami
摘要
Large language models (LLMs) tuned for safety often avoid acknowledging demographic differences, even when such acknowledgment is factually correct (e.g., ancestry-based disease incidence) or contextually justified (e.g., religious hiring preferences). This identity-blindness yields incorrect res...