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dct:title "Synergizing LLM Agents and Knowledge Graph for Socioeconomic Prediction in LBSN";
<http://purl.org/spar/cito/describes> <https://neverblink.eu/ontologies/llm-kg/methods#SynergizeLLMAgentAndKnowledgeGraphLearningModelSLAK>;
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dct:subject <https://neverblink.eu/ontologies/llm-kg/categories#SynergizedReasoning>;
rdfs:comment "The SLAK framework synergizes LLM agents and a Location-Based Knowledge Graph (LBKG) for socioeconomic prediction. It leverages LLM agents' reasoning capabilities for automatic discovery and optimization of task-relevant meta-paths within the LBKG, and employs a semantic-guided knowledge fusion module for adaptive knowledge integration using LLM embeddings. Furthermore, it introduces a cross-task communication mechanism enabling both LLM agent-level collaboration for meta-path refinement and KG embedding-level fusion, positioning the LLMs as agents interacting with KGs for enhanced reasoning.";
rdfs:label "Synergize LLM Agent and Knowledge Graph learning model (SLAK)";
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