KG-WISE decomposes GNN models and uses LLM-generated query templates for partial loading of relevant components, achieving up to 28x faster inference and 98% lower memory on KGs with up to 42 million nodes while preserving accuracy.
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2026 2verdicts
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An LLM-supported framework maps natural-language commands to distinguishable Apollo lane-change parameters for three driving styles via clustering and RAG, with experiments showing improved interpretation of implicit preferences.
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An LLM-Guided Query-Aware Inference System for GNN Models on Large Knowledge Graphs
KG-WISE decomposes GNN models and uses LLM-generated query templates for partial loading of relevant components, achieving up to 28x faster inference and 98% lower memory on KGs with up to 42 million nodes while preserving accuracy.
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A Large-Language-Model Supported Personalized Driving Framework for Lane Change in Highway Scenarios
An LLM-supported framework maps natural-language commands to distinguishable Apollo lane-change parameters for three driving styles via clustering and RAG, with experiments showing improved interpretation of implicit preferences.