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arXiv — cs.AI preprintsInternational15 October 2026

SuperAI: Merging Capabilities Across Heterogeneous Foundation Models

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arXiv:2610.15322v2 Announce Type: new Abstract: Enabling the reuse and composition of knowledge and capabilities distributed across foundation models is an important step toward building scalable artificial intelligence (AI) systems. However, architectural differences and incompatible representations make it difficult to transfer and integrate these capabilities through a unified cross-model interface. To address this challenge, we propose SuperAI, a cross-architecture multi-model fusion framework that integrates complementary capabilities from multiple source models into a host model through
— arXiv — cs.AI preprints

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