WxxShirley/GNN4TaskPlan

[NeurIPS 2024] Official implementation for paper "Can Graph Learning Improve Planning in LLM-based Agents?"

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Emerging

This project helps integrate Graph Neural Networks (GNNs) with Large Language Models (LLMs) to improve how LLMs plan and break down complex user requests into actionable steps. It takes a complex user request as input and outputs a more efficient, accurate sequence of sub-tasks for the LLM to execute. This is for AI researchers and developers working on building more robust and reliable LLM-based agents.

151 stars. No commits in the last 6 months.

Use this if you are developing LLM-based agents and find that current LLMs struggle with complex decision-making and planning, especially when sub-tasks have dependencies that can be modeled as a graph.

Not ideal if you are looking for a plug-and-play solution for general-purpose LLM improvements without diving into graph-based planning or agent architecture.

LLM-based agents AI planning task decomposition graph neural networks decision-making
Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 10 / 25
Maturity 16 / 25
Community 12 / 25

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Stars

151

Forks

12

Language

Python

License

MIT

Last pushed

May 11, 2025

Commits (30d)

0

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