GR-SAP: Generative Replay for Safety Alignment Preservation during Fine-Tuning
The episode discusses the GR-SAP paper, which addresses safety drift during LLM fine-tuning. Instead of relying on static data, authors propose a generative replay mechanism. This method trains models by actively simulating and practicing responses to borderline unsafe scenarios, ensuring high performance without compromising core safety alignment.