How can I route queries efficiently across LLMs for accurate answers?
Talk to Right Specialists: Routing and Planning in Multi-agent System for Question Answering
This paper introduces RopMura, a multi-agent system for question answering that uses multiple specialized Large Language Models (LLMs) augmented with retrieval (RAG). Each agent has its own knowledge base and expertise. RopMura addresses the challenges of efficiently routing questions to the right agents and planning multi-step reasoning across different knowledge domains. Key points for LLM-based multi-agent systems include a novel routing mechanism based on knowledge clustering and similarity comparison, and a flexible, iterative planning strategy that decomposes complex queries and dynamically adjusts to new information, overcoming limitations of existing rigid or single-agent approaches. This enables effective collaboration between specialized LLMs without sharing the underlying data, addressing knowledge sovereignty concerns.