Research on integrating Large Language Models with Knowledge Graphs is categorized into several distinct approaches: Pre-training, Fine-Tuning, KG-Augmented Prompting, Retrieval-Augmented Generation (RAG), Graph RAG, KG RAG, Hybrid RAG, Spatial RAG, Offline/Online KG Guidelines, Agent-based KG Guidelines, KG-Driven Filtering and Validation, Visual Question Answering (VQA), Multi-Document QA, Multi-Hop QA, Conversational QA, Temporal QA, Multilingual QA, Index-based Optimization, and Natural Language to Graph Query Language (NL2GQL).

Authors

• Person: Not available Organization: GitHub
  LLM-KG4QA: Large Language Models and Knowledge Graphs for ...

Sources

• LLM-KG4QA: Large Language Models and Knowledge Graphs for ... github.com GitHub via serper

Referenced by nodes (5)

• Retrieval-Augmented Generation (RAG) concept
• fine-tuning concept
• multi-hop knowledge base question answering concept
• Pre-training concept
• Visual Question Answering concept