[NeurIPS'24] HippoRAG is a novel RAG framework inspired by human long-term memory that enables LLMs to continuously integrate knowledge across external documents. RAG + Knowledge Graphs + Personalized PageRank.

[Paper List] Papers integrating knowledge graphs (KGs) and large language models (LLMs)

The python library for research and development in NLP, multimodal LLMs, Agents, ML, Knowledge Graphs, and more.

In this project, I explored how to extract knowledge graphs from text using LLMs, such as OpenAI GPT4o.

Transform unstructured text into structured knowledge with LLMs. Graphs, hypergraphs, and spatio-temporal extractions — with one command.

Create knowledge graphs with LLMs

MedReason: Eliciting Factual Medical Reasoning Steps in LLMs via Knowledge Graphs

GraphRAG-rs is a high-performance, state-of-the-art Rust implementation of GraphRAG (Graph-based Retrieval Augmented Generation) that builds knowledge graphs from documents and enables natural language querying with configurable entity extraction and local LLM integration

Integrating knowledge graphs (KG) with large language models (LLM)

LLM-KG4QA: Large Language Models and Knowledge Graphs for Question Answering

AI-native codebase intelligence skills — generate persistent .nexus-map/ knowledge bases and instantly query file structure, dependency graphs, and change impact. Built for Copilot, Cursor, and any tool-calling LLM. 面向 AI 编程助手的代码库感知技能——生成持久化知识图谱，精准查询文件结构、依赖关系与改动影响半径。

We want to try and evaluate LLMs using Knowledge Graphs

Code for the Manning book: Knowledge Graphs and LLMs in Action

CTINexus is a framework that leverages optimized in-context learning of LLMs to enable data-efficient extraction of cyber threat intelligence and the construction of high-quality cybersecurity knowledge graphs.

The long-term memory for your Superagents 🥷and LLMs 🤖. Built with GraphRAG, Knowledge graphs and autonomous ai agents

An advanced retrieval system that combines semantic vector search with token-based search, using contextual chunking and knowledge graphs to improve accuracy. It ensures precise query responses with LLM-based answer checking and graph visualization.

LightPROF: A Lightweight Reasoning Framework for LLMs on Knowledge Graphs

CypherBench: Towards Precise Retrieval over Full-scale Modern Knowledge Graphs in the LLM Era

The EscherGraph introduces advanced search capabilities on generalized knowledge graphs that are build using LLMs.

Interesting Scientific Idea Generation Using Knowledge Graphs and LLMs: Evaluations with 100 Research Group Leaders

A collection of interesting links, articles, research papers and projects related to knowledge graphs, GenAI and LLMs (large language models)

Getting started with BAML for creating and querying knowledge graphs with LLMs

Reasoning LLM-Enhanced Database Operation and Maintenance System using Knowledge Graphs

[ICLR'26] AtlasKV: A scalable, effective, and general way to augment LLMs with billion-scale knowledge graphs using very little GPU memory cost.

"Head-to-Tail How Knowledgeable are Large Language Models (LLMs)? A.K.A. Will LLMs Replace Knowledge Graphs?" (NAACL 2024)

LLM-Driven Ontology Construction for Enterprise Knowledge Graphs.

🧠 AI Second Brain — 100% Local Knowledge Management Private, self-hosted second brain. Store, search, and synthesize documents, images, and ideas with local LLMs (LLaVA, CLIP) and PostgreSQL + pgvector. Features multimodal search, knowledge graphs, gDrive streaming, and real-time analysis — all offline, no API keys, no cloud, no limits.

Prompt-based pipeline for extracting procedural knowledge graphs from text with LLMs

This project compares manually curated knowledge graphs with those automatically generated by Ollama Gemma 7B, a large language model (LLM). By analyzing their differences and similarities, this research provides insights into the strengths and limitations of both manual and AI-based approaches to knowledge graph generation.

Build knowledge graphs from biomedical literature and query them with an LLM agent