AI RESEARCH
Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models
arXiv CS.LG
•
ArXi:2605.15706v1 Announce Type: new Recent advances in Large Language Models (LLMs) have catalyzed the development of multi-agent systems (MAS) for complex reasoning tasks. However, existing MAS typically rely on pre-defined or pre-compiled communication topologies, which limits their flexibility and adaptability to dynamic task requirements. In this work, we propose Differentiable Mixture-of-Agents (DMoA), a self-evolving multi-agent framework that enables elastic and adaptive agent collaboration during inference.