concept

external knowledge base

Also known as: external knowledge sources, external knowledge, external knowledge source, external knowledge base

Facts (11)

Sources

Neuro-Symbolic AI: Explainability, Challenges, and Future Trends arxiv.org arXiv Nov 7, 2024 2 facts

referenceKislay Raj proposed a neuro-symbolic approach to enhance the interpretability of graph neural networks by integrating external knowledge, presented at the 32nd ACM International Conference on Information and Knowledge Management.

referenceEhud Karpas, Omri Abend, Yonatan Belinkov, Barak Lenz, Opher Lieber, Nir Ratner, Yoav Shoham, Hofit Bata, Yoav Levine, Kevin Leyton-Brown, et al. authored 'MRKL Systems: A modular, neuro-symbolic architecture that combines large language models, external knowledge sources and discrete reasoning', published as an arXiv preprint (arXiv:2205.00445) in 2022.

Awesome-Hallucination-Detection-and-Mitigation - GitHub github.com GitHub 1 fact

referenceThe paper "Bridging External and Parametric Knowledge: Mitigating Hallucination of LLMs with Shared-Private Semantic Synergy in Dual-Stream Knowledge" by Sui et al. (2025) proposes a method to mitigate hallucinations in large language models by bridging external and parametric knowledge using shared-private semantic synergy.

Empowering GraphRAG with Knowledge Filtering and Integration arxiv.org arXiv Mar 18, 2025 1 fact

claimLarge language models can use attention scores as a natural indicator of the relevance and significance of retrieved external knowledge, as supported by Yang et al. (2024) and Ben-Artzy and Schwartz (2024).

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

claimRetrieval-Augmented Generation (RAG) is a technique that enhances an LLM's response by pulling in relevant information from an external knowledge source.

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

procedureExternal knowledge bases can be queried to enhance knowledge graph data by using extracted global persistent identifiers (PID) such as ISBN numbers, DOIs, or ORCIDs to request information from Wikidata.

On Hallucinations in Artificial Intelligence–Generated Content ... jnm.snmjournals.org The Journal of Nuclear Medicine 1 fact

claimShi et al. improved AI output quality by reformulating complex medical questions into search-optimized synthetic queries to retrieve external knowledge.

Building Trustworthy NeuroSymbolic AI Systems - arXiv arxiv.org arXiv 1 fact

claimIncorporating external knowledge into an ensemble of Large Language Models (LLMs) aims to improve logical coherence by ensuring generated content aligns with established facts and relationships in external knowledge sources.

LLM Hallucination Detection and Mitigation: State of the Art in 2026 zylos.ai Zylos Jan 27, 2026 1 fact

claimRetrieval-Augmented Generation (RAG) reduces hallucinations by grounding responses in external knowledge sources, though it can introduce new hallucinations through poor retrieval quality, context overflow, or misaligned reranking.

The Synergy of Symbolic and Connectionist AI in LLM-Empowered ... arxiv.org arXiv Jul 11, 2024 1 fact

referenceEhud Karpas et al. proposed MRKL systems, a modular, neuro-symbolic architecture that integrates large language models with external knowledge sources and discrete reasoning capabilities.

Practices, opportunities and challenges in the fusion of knowledge ... frontiersin.org Frontiers 1 fact

referenceKGValidator, proposed by Boylan et al. in 2024, is a consistency and validation framework for knowledge graphs that uses generative models and supports any external knowledge source.