Matches in Nanopublications for { <https://neverblink.eu/ontologies/llm-kg/methods#KgRetriever> ?p ?o ?g. }
Showing items 1 to 7 of
7
with 100 items per page.
- KgRetriever type Workflow assertion.
- KgRetriever type Workflow assertion.
- KgRetriever label "KG Retriever" assertion.
- KgRetriever label "KG-Retriever" assertion.
- KgRetriever 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. This directly aligns with using KGs to enhance LLM performance during inference." assertion.
- KgRetriever subject KGEnhancedLLMInference assertion.
- KgRetriever hasTopCategory KGEnhancedLLM assertion.