DMoA is a differentiable multi-agent LLM framework with recurrent context-aware routing and predictive entropy self-supervision that claims SOTA results on 9 benchmarks through elastic agent collaboration.
Rmoa: Optimizing mixture-of-agents through diversity maximization and residual compensation
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Differentiable Mixture-of-Agents Incentivizes Swarm Intelligence of Large Language Models
DMoA is a differentiable multi-agent LLM framework with recurrent context-aware routing and predictive entropy self-supervision that claims SOTA results on 9 benchmarks through elastic agent collaboration.