https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o/Head https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o http://www.nanopub.org/nschema#hasAssertion https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o/assertion https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o http://www.nanopub.org/nschema#hasProvenance https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o/provenance https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o http://www.nanopub.org/nschema#hasPublicationInfo https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o/pubinfo https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.nanopub.org/nschema#Nanopublication https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o/assertion https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/dc/terms/title KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/describes https://neverblink.eu/ontologies/llm-kg/methods#KgRetriever https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/describes https://neverblink.eu/ontologies/llm-kg/methods#KgRetrieverEntityLevelKgConstructionUsingLlms https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#Bm25 https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#DenseRetriever https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#GraphGuidedReasoning https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#IterRetgen https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#Itrg https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#Kgp https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#LlmWithCoT https://doi.org/10.48550/arXiv.2412.05547 http://purl.org/spar/cito/discusses https://neverblink.eu/ontologies/llm-kg/methods#NaiveLlm https://doi.org/10.48550/arXiv.2412.05547 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://www.w3.org/ns/prov#Entity https://neverblink.eu/ontologies/llm-kg/methods#Bm25 http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#Bm25 http://www.w3.org/2000/01/rdf-schema#label BM25 https://neverblink.eu/ontologies/llm-kg/methods#DenseRetriever http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#DenseRetriever http://www.w3.org/2000/01/rdf-schema#label DenseRetriever https://neverblink.eu/ontologies/llm-kg/methods#GraphGuidedReasoning http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#GraphGuidedReasoning http://www.w3.org/2000/01/rdf-schema#label Graph-guided reasoning https://neverblink.eu/ontologies/llm-kg/methods#IterRetgen http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#IterRetgen http://www.w3.org/2000/01/rdf-schema#label ITER-RETGEN https://neverblink.eu/ontologies/llm-kg/methods#Itrg http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#Itrg http://www.w3.org/2000/01/rdf-schema#label ITRG https://neverblink.eu/ontologies/llm-kg/methods#KgRetriever http://purl.org/dc/terms/subject https://neverblink.eu/ontologies/llm-kg/categories#KGEnhancedLLMInference https://neverblink.eu/ontologies/llm-kg/methods#KgRetriever http://www.w3.org/1999/02/22-rdf-syntax-ns#type http://purl.org/spar/fabio/Workflow https://neverblink.eu/ontologies/llm-kg/methods#KgRetriever http://www.w3.org/2000/01/rdf-schema#comment KG-Retriever is a novel Retrieval-Augmented Generation (RAG) framework that leverages a Hierarchical Index Graph (HIG) to provide comprehensive and efficient knowledge to LLMs during the inference stage. Its goal is to improve the quality, credibility, and efficiency of LLM-generated responses by addressing challenges like multi-hop question answering and information fragmentation. 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