Adaptive selection and dynamic weighted fusion of source LLMs reduces knowledge interference and improves target model accuracy compared to FuseLLM.
Chinese-vicuna: A chinese instruction-following llama-based model
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Enabling Flexible Multi-LLM Integration for Scalable Knowledge Aggregation
Adaptive selection and dynamic weighted fusion of source LLMs reduces knowledge interference and improves target model accuracy compared to FuseLLM.