VQV Signal
SKIMIX is a multi-agent framework where agents with diverse skill sets collaborate via iterative refinement, using embedding-based skill retrieval, anti-dilution routing, and adaptive skill evolution. It improves performance across six reasoning benchmarks by effectively selecting, combining, and m...
SKIMIX is a multi-agent framework where agents with diverse skill sets collaborate via iterative refinement, using embedding-based skill retrieval, anti-dilution routing, and adaptive skill evolution. It improves performance across six reasoning benchmarks by effectively selecting, combining, and m...
AI-assisted summary based on the listed source.
AI agents increasingly rely on large skill libraries, but selecting, combining, and maintaining skills remains difficult. We propose SKIMIX, a multi-agent framework in which agents with different skill portfolios collaborate through iterative refinement. SKIMIX combines embedding-based skill retrieval, submodular...
Managing large skill libraries in AI agents is challenging, and SKIMIX offers a structured approach to dynamically harness and evolve skills through multi-agent collaboration. This can enhance the adaptability and reasoning capabilities of AI systems.
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