Matches in Nanopublications for { ?s ?p ?o <https://w3id.org/np/RAk8AYwhOQ4k6JOAlHHGKVuB7TsBcKobmpnjMETsvc_1o/assertion>. }
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- KgRetriever type Workflow assertion.
- arXiv.2412.05547 type Entity assertion.
- Bm25 type Workflow assertion.
- DenseRetriever type Workflow assertion.
- GraphGuidedReasoning type Workflow assertion.
- IterRetgen type Workflow assertion.
- Itrg type Workflow assertion.
- KgRetrieverEntityLevelKgConstructionUsingLlms type Workflow assertion.
- Kgp type Workflow assertion.
- LlmWithCoT type Workflow assertion.
- NaiveLlm type Workflow assertion.
- KgRetriever label "KG-Retriever" assertion.
- Bm25 label "BM25" assertion.
- DenseRetriever label "DenseRetriever" assertion.
- GraphGuidedReasoning label "Graph-guided reasoning" assertion.
- IterRetgen label "ITER-RETGEN" assertion.
- Itrg label "ITRG" assertion.
- KgRetrieverEntityLevelKgConstructionUsingLlms label "KG-Retriever's Entity-Level KG Construction using LLMs" assertion.
- Kgp label "KGP" assertion.
- LlmWithCoT label "LLM with CoT" assertion.
- NaiveLlm label "Naive LLM" 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.
- KgRetrieverEntityLevelKgConstructionUsingLlms comment "This method describes the specific use of large language models (Qwen-72B) with in-context learning and designed prompts to extract entities and relations from unstructured text within documents. This process is crucial for constructing the entity-level knowledge graph layer of the Hierarchical Index Graph within the KG-Retriever framework, directly using LLMs to perform a core KG construction task." assertion.
- arXiv.2412.05547 describes KgRetriever assertion.
- arXiv.2412.05547 describes KgRetrieverEntityLevelKgConstructionUsingLlms assertion.
- arXiv.2412.05547 discusses Bm25 assertion.
- arXiv.2412.05547 discusses DenseRetriever assertion.
- arXiv.2412.05547 discusses GraphGuidedReasoning assertion.
- arXiv.2412.05547 discusses IterRetgen assertion.
- arXiv.2412.05547 discusses Itrg assertion.
- arXiv.2412.05547 discusses Kgp assertion.
- arXiv.2412.05547 discusses LlmWithCoT assertion.
- arXiv.2412.05547 discusses NaiveLlm assertion.
- KgRetriever subject KGEnhancedLLMInference assertion.
- KgRetrieverEntityLevelKgConstructionUsingLlms subject LLMAugmentedKGConstruction assertion.
- arXiv.2412.05547 title "KG-Retriever: Efficient Knowledge Indexing for Retrieval-Augmented Large Language Models" assertion.
- KgRetriever hasTopCategory KGEnhancedLLM assertion.
- KgRetrieverEntityLevelKgConstructionUsingLlms hasTopCategory LLMAugmentedKG assertion.