Matches in Nanopublications for { ?s ?p ?o <https://w3id.org/np/RA_hODdkskEF6yC46tSWakRpBEHFeUjdL6QYX30S65YQs/assertion>. }
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- arXiv.2508.14427 type Entity assertion.
- DRAGON type Workflow assertion.
- KGLM type Workflow assertion.
- KGSFT type Workflow assertion.
- KnowledgeGraphInfusedFineTuningFramework type Workflow assertion.
- DRAGON label "DRAGON" assertion.
- KGLM label "KGLM" assertion.
- KGSFT label "KG-SFT" assertion.
- KnowledgeGraphInfusedFineTuningFramework label "Knowledge Graph-Infused Fine-Tuning Framework" assertion.
- KnowledgeGraphInfusedFineTuningFramework comment "This method proposes a fine-tuning algorithm framework that injects knowledge graph information into large language models during the fine-tuning stage. It uses a GNN to encode KG information, a fusion mechanism to combine KG embeddings with LLM representations, a gating mechanism to balance contributions, and a joint loss function. The primary goal is to improve the LLM's knowledge expression and structured reasoning capabilities." assertion.
- arXiv.2508.14427 describes KnowledgeGraphInfusedFineTuningFramework assertion.
- arXiv.2508.14427 discusses DRAGON assertion.
- arXiv.2508.14427 discusses KGLM assertion.
- arXiv.2508.14427 discusses KGSFT assertion.
- KnowledgeGraphInfusedFineTuningFramework subject KGEnhancedLLMPretraining assertion.
- arXiv.2508.14427 title "Knowledge Graph-Infused Fine-Tuning for Structured Reasoning in Large Language Models" assertion.
- KnowledgeGraphInfusedFineTuningFramework hasTopCategory KGEnhancedLLM assertion.