A structured survey organizing graph-LLM integration methods by purpose, modality, and strategy across application domains.
Iterative Zero-Shot LLM Prompting for Knowledge Graph Construction
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Using LLM extraction on 681 papers, the authors build a public knowledge graph showing financial NLP moved from LLM adoption to limitation-aware, modular system design between 2022 and 2025.
A multi-step LLM-based pipeline constructs the first knowledge graph for nuclear fusion energy and enables RAG for multi-hop queries.
The paper surveys PLM-based knowledge graph construction and proposes the LLHKG framework claiming that lightweight LLMs achieve KG construction performance comparable to GPT-3.5.
Domain-specific fine-tuning of an LLM for NER-RE on human-smuggling court texts yields 15.5% and 31.46% absolute F1 gains over a larger baseline, with reduced noise, duplication, and runtime.
citing papers explorer
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Integrating Graphs, Large Language Models, and Agents: Reasoning and Retrieval
A structured survey organizing graph-LLM integration methods by purpose, modality, and strategy across application domains.
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MetaGraph: A Large-Scale Meta-Analysis of GenAI in Financial NLP (2022-2025)
Using LLM extraction on 681 papers, the authors build a public knowledge graph showing financial NLP moved from LLM adoption to limitation-aware, modular system design between 2022 and 2025.
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Automated Construction of a Knowledge Graph of Nuclear Fusion Energy for Effective Elicitation and Retrieval of Information
A multi-step LLM-based pipeline constructs the first knowledge graph for nuclear fusion energy and enables RAG for multi-hop queries.
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Construction of Knowledge Graph based on Language Model
The paper surveys PLM-based knowledge graph construction and proposes the LLHKG framework claiming that lightweight LLMs achieve KG construction performance comparable to GPT-3.5.
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FineREX: Fine-Tuned NER-RE for Human Smuggling Knowledge Graphs
Domain-specific fine-tuning of an LLM for NER-RE on human-smuggling court texts yields 15.5% and 31.46% absolute F1 gains over a larger baseline, with reduced noise, duplication, and runtime.