OPERA: A Reinforcement Learning--Enhanced Orchestrated Planner-Executor Architecture for Reasoning-Oriented Multi-Hop Retrieval

In three linesOPERA is a retrieval-augmented generation (RAG) architecture coupling planning and execution via reinforcement learning. A Goal Planning Module decomposes complex questions into sub-goals, executed by a Reason-Execute Module with specialized components for reasoning and retrieval. Training uses MAPGRPO, a GRPO variant. Superior results on complex multi-hop benchmarks.

Summary generated by Claude — human-verified