PRISMA: Reinforcement Learning Guided Two-Stage Policy Optimization in Multi-Agent Architecture for Open-Domain Multi-Hop QA

Proposes a decoupled multi-agent RAG framework for multi-hop QA with a Plan-Retrieve-Inspect-Solve-Memoize architecture and two-stage GRPO optimization to address retrieval collapse over large corpora.