6 entries
Keyword: knowledge-graphsArticle:Exxact
Vector-based RAG falls short when handling structured schemas, complex logic, or dynamic real-time data. An article by Exxact highlights three architectural alternatives: Structured Retrieval RAG, API-Augmented RAG, and Knowledge-Based RAG.
Article:digitalocean.com
Standard RAG pipelines rely on text embeddings and vector databases, but they incur substantial operational overhead, cost, and semantic limitations. This article explores embedding-free alternatives such as lexical search, LLM-driven iterative exploration, knowledge graphs, and prompt-based navigation.
Article:Lei Liang et al.
A research team led by Lei Liang introduces Knowledge Augmented Generation (KAG), a framework extending conventional RAG with knowledge graphs to address logic, temporal, and numerical reasoning deficits in specialised domains.
Repository:OSU-NLP-Group/HippoRAG
HippoRAG (now in version 2) is an open-source memory framework for LLMs developed by the OSU NLP Group, combining knowledge graphs and Personalized PageRank to mimic human long-term memory across external documents.
4kstarsPython
X post:CyrilXBT
In a detailed thread, CyrilXBT outlines a curriculum for prospective Graph Architects, combining structured knowledge graphs with state-machine graphs for AI agents to improve on basic RAG and opaque reasoning loops.
725bookmarks67.3kviews
VideoVideo:Greg Isenberg
Greg Isenberg breaks down graph engineering as the layer above prompt and context engineering. Rather than running complex tasks through a single chat prompt, work is structured into discrete jobs, parallel paths, independent checks, and human approvals. In addition to distinguishing knowledge graphs from agent graphs, he demonstrates practical workflow patterns and three implementation levels ranging from manual runs to tools like LangGraph and n8n.
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