hayulalab/swarm-orchestration-paper

Orchestration Over Scale: Five Strategies for Frontier-Level AI Without Trillion-Parameter Models — Hayula Research

Hayula AI Lab

Abstract

Trillion-parameter models (GPT-5, Claude Opus 4, Gemini 2.5 Pro) exhibit emergent capabilities through scale-induced information density. An ensemble of small specialists cannot replicate the weights of a 1T model, but it can replicate its behavior through structured orchestration. This paper presents five practical strategies — multi-specialist consensus, progressive chaining, ACE self-improvement loops, synthetic data generation, and DRAGON hierarchical orchestration — that together enable fro

Files

File	Description
paper.md	Full paper (Markdown)
README.md	This model card

Citation

@techreport{hayulalab2026swarmorchestration,
    title={Orchestration Over Scale: Five Strategies for Frontier-Level AI Without Trillion-Parameter Models — Hayula Research},
    author={Hayula AI Lab},
    year={2026},
    url={https://huggingface.co/hayulalab/swarm-orchestration-paper}
}

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