AIBullisharXiv – CS AI · 14h ago7/10
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Beyond Consensus: Trace-Level Synthesis in Mixture of Agents
Researchers demonstrate that aggregating complete reasoning traces from multiple LLM agents recovers correct solutions more effectively than majority voting, even when agents unanimously agree. A new approach called Self-Consistent Mixture of Agents uses semantic-preserving perturbations to generate trace diversity while maintaining safety guarantees, outperforming heterogeneous model ensembles across mathematical and scientific reasoning tasks.