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SkewRoute: Training-Free LLM Routing for Knowledge Graph Retrieval-Augmented Generation via Score Skewness of Retrieved Context

A training-free routing framework for knowledge graph retrieval-augmented generation.

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SkewRoute: Training-Free LLM Routing for Knowledge Graph Retrieval-Augmented Generation via Score Skewness of Retrieved Context

By Association for Computational Linguistics 2025, Cao, Yukun, Feng, Yuan, Wang, Hairu, Xie, Xike, Zhou, S. KevinOpen MIND
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The paper proposes a novel, training-free routing framework called SkewRoute. It is tailored to knowledge graph retrieval-augmented generation (KG-RAG) and effectively balances performance and cost. The method reduces calls to larger LLMs by up to 50% without sacrificing response quality.

Abstract

The paper proposes a novel, training-free routing framework called SkewRoute. It is tailored to knowledge graph retrieval-augmented generation (KG-RAG) and effectively balances performance and cost. The method reduces calls to larger LLMs by up to 50% without sacrificing response quality.

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llm routingkg ragtraining-freeskewrouteknowledge graph retrieval-augmented generationKnowledge GraphsRetrieval & RAGLarge Language ModelsSemantic Interoperability
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