Reinforcing privacy reasoning in LLMs via normative simulacra from fiction

This paper proposes a novel method to enhance privacy reasoning in LLMs by extracting normative simulacra from fiction novels. The approach involves fine-tuning LLMs via supervised learning followed by GRPO reinforcement learning, using a composite reward function to align information handling practices with user privacy expectations.