concept

graph

Also known as: graph, graphs

Facts (11)

Sources

Empowering GraphRAG with Knowledge Filtering and Integration arxiv.org arXiv Mar 18, 2025 2 facts

referenceMufei Li, Siqi Miao, and Pan Li authored 'Simple is effective: The roles of graphs and large language models in knowledge-graph-based retrieval-augmented generation', published in the International Conference on Learning Representations.

referenceLinhao Luo, Yuan-Fang Li, Gholamreza Haffari, and Shirui Pan authored 'Reasoning on graphs: Faithful and interpretable large language model reasoning', published in the International Conference on Learning Representations.

A survey on augmenting knowledge graphs (KGs) with large ... link.springer.com Springer Nov 4, 2024 2 facts

referenceHamilton, Ying, and Leskovec authored 'Representation learning on graphs: methods and applications', an arXiv preprint published in 2017 (arXiv:1709.05584).

referenceFatemi, Halcrow, and Perozzi authored 'Talk like a graph: encoding graphs for large language models', an arXiv preprint published in 2023 (arXiv:2310.04560).

Unlocking the Potential of Generative AI through Neuro-Symbolic ... arxiv.org arXiv Feb 16, 2025 1 fact

claimMethods such as Graph Neural Networks (GNNs), Named Entity Recognition (NER), link prediction, and relation extraction fall into the Neuro[Symbolic] category because they leverage symbolic relationships like ontologies or graphs to enhance neural processing.

Track: Poster Session 3 - aistats 2026 virtual.aistats.org Samuel Tesfazgi, Leonhard Sprandl, Sandra Hirche · AISTATS 1 fact

claimRelational data, such as graphs, often disobey the Independent and Identically Distributed (IID) condition, which complicates the Out-of-Distribution problem, particularly when temporal data is involved.

Construction of Knowledge Graphs: State and Challenges - arXiv arxiv.org arXiv 1 fact

procedureThe KARMA system provides a semi-automatic approach to link a structured source, such as a relational database, with an existing ontology. The process consists of four steps: (1) assigning semantic types to each column, (2) constructing a graph of all possible mappings between the source and the ontology, (3) refining the model based on user input, and (4) generating a formal specification of the source model.

Quantum Approaches to Consciousness plato.stanford.edu Stanford Encyclopedia of Philosophy Nov 30, 2004 1 fact

referenceAtmanspacher H. and Filk T. published 'Complexity and non-commutativity of learning operations on graphs' in BioSystems in 2006.

RAG Using Knowledge Graph: Mastering Advanced Techniques procogia.com Procogia Jan 15, 2025 1 fact

codeThe Neo4jVector.from_existing_graph method creates a vector index from an existing graph by specifying the embedding model, search type, node label, text node properties, and embedding node property.

How NebulaGraph Fusion GraphRAG Bridges the Gap Between ... nebula-graph.io NebulaGraph Jan 27, 2026 1 fact

claimConstructing, maintaining, and querying a graph for RAG is historically complex and resource-intensive, often requiring specialized infrastructure and expertise, making it more costly than vector-based approaches.

LLM-Powered Knowledge Graphs for Enterprise Intelligence and ... arxiv.org arXiv Mar 11, 2025 1 fact

referenceJin, B., Liu, G., Han, C., Jiang, M., Ji, H., and Han, J. authored the arXiv preprint 'Large language models on graphs: A comprehensive survey' (arXiv:2312.02783) in 2024.