Researchers find simple random routing improves Multi-Agent debate efficiency
A new paper on arXiv challenges the assumption that complex communication topologies are needed for multi-agent debate (MAD) to improve large language model reasoning. The authors propose a baseline method: each agent debates two distinct, randomly selected peers in every round. Their findings show this approach achieves competitive accuracy at lower cost than more sophisticated methods.
Key points
- Random-without-replacement routing—each agent debates two new peers per round—matches complex methods in accuracy but cuts costs
- Lightweight stopping criteria reduce inference costs by up to an unspecified amount while preserving accuracy
- Authors urge evaluating advanced topology control against these simple baselines before adopting it
The study also explores lightweight stopping criteria to further reduce inference costs without sacrificing accuracy. The authors argue that advanced topology control mechanisms should be benchmarked against these simpler baselines before justifying their added complexity. The work does not introduce a new model or tool but offers insights into optimizing MAD systems.
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