# XiaoxinHe/Awesome-Graph-LLM

A collection of AWESOME things about Graph-Related LLMs.

Repository: https://github.com/XiaoxinHe/Awesome-Graph-LLM
Canonical: https://ross.abutalabs.com/products/awesome-graph-llm
License: MIT
License Family: permissive
Last push: 2025-11-05T13:18:47+00:00

## Health v2 (maintenance only)
Score: 52/100 (v2, computed 2026-09-02T17:46:02.011165+00:00)
- activity 50, release rhythm 35, longevity 84
- inputs: {"age_days": 1185, "days_push": 301, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 2446, forks 166 (observed 2026-08-28T04:06:52.674659+00:00)

## What it is
A curated awesome-list of research papers, benchmarks, and resources on the intersection of graph structures and large language models. It covers topics like graph prompting, knowledge graphs, GraphRAG, and multi-agent systems.

## Use cases
- find research papers on graph large language models
- learn about GraphRAG techniques
- find benchmarks for LLM graph reasoning
- survey knowledge graph and LLM integration
- find datasets of textual-edge graphs
- research graph-based multi-agent systems

## When to choose
- you need a curated reading list on graph-LLM research
- you are surveying GraphRAG or knowledge graph + LLM methods
- you want benchmarks and datasets for graph reasoning with LLMs

## When to avoid
- you need runnable software or a library
- you want graph neural network implementations rather than papers

## Facets
- artifact type: learning-resource
- maturity: active
- function: documentation
- domain: large-language-models, artificial-intelligence, graph-processing, tutorials
- platform: cross-platform
- tags: awesome-list, graph-llm, graphrag, knowledge-graph, research-papers, graph-neural-networks

## Member repositories
- XiaoxinHe/Awesome-Graph-LLM (main) score 52

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:06:52.674659+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T02:30:32.494847+00:00, confidence not recorded.
  - readme: https://github.com/XiaoxinHe/Awesome-Graph-LLM (fetched 2026-08-28T04:06:52.674659+00:00, sha 5c85f88d9d79)
- Data as of 2026-08-30T08:39:29.467469+00:00.