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By merging models on the Fisher-Rao manifold, this work achieves stable and accurate LLM merging even with many heterogeneous models, overcoming the representation collapse issues plaguing simpler weight averaging techniques.
SkillOrchestra slashes the learning costs of AI agent orchestration by up to 700x while improving performance by explicitly modeling agent skills and costs, offering a more scalable and interpretable alternative to RL-based methods.
