Roleplay-doh: Enabling Domain-Experts to Create LLM-simulated Patients via Eliciting and Adhering to Principles

Understand

Recent works leverage LLMs to roleplay realistic social scenarios, aiding novices in practicing their social skills.

• However, simulating sensitive interactions, such as in mental health, is challenging.
• Privacy concerns restrict data access, and collecting expert feedback, although vital, is laborious.
• To address this, we develop Roleplay-doh, a novel human-LLM collaboration pipeline that elicits qualitative feedback from a domain-expert, which is transformed into a set of principles, or natural language rules, that govern an LLM-prompted roleplay.