SOURCE-LINKED INTELLIGENCE

PersonaForge: Realistic Multi-Turn User Simulation for Agentic Systems

arXiv · AI, language, vision and robotics · article · Aug 28, 2026 · UTC

Large language models are increasingly used as agentic workflow executors, yet existing training data and benchmarks largely assume informationally complete, single-turn queries. Our analysis of 16K real-world sessions shows that 75.9% of interactions are multi-turn, revealing a substantial gap between how users interact with agents and how such systems are trained and evaluated. We introduce \textbf{PersonaForge}, a user simulation framework for synthesizing realistic multi-turn user--agent interactions. PersonaForge combines a four-dimensional persona space, SOUL-driven behavioral control ca

Read original source ↗ Open in workspace

recordType

paper

region

Global