WxxShirley/LLMNodeBed

[ICML 2025] Official implementation for paper "A Comprehensive Analysis on LLM-based Node Classification Algorithms"

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Experimental

This project offers a standardized way to compare how well different large language model (LLM) approaches classify 'nodes' within network data. It takes in various network datasets and outputs a performance evaluation for 8 different LLM-based algorithms, helping researchers or data scientists understand which methods are most effective for their specific graph-structured data classification tasks.

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Use this if you are a researcher or data scientist evaluating or developing new LLM-based methods for classifying items in a network, such as categorizing documents based on citation networks or users in social graphs.

Not ideal if you need a plug-and-play solution for general text classification or if you are not working with graph-structured data and LLMs for classification.

network-analysis graph-data-classification large-language-models machine-learning-research data-science-benchmarking
No License Stale 6m No Package No Dependents
Maintenance 2 / 25
Adoption 8 / 25
Maturity 8 / 25
Community 8 / 25

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Language

Python

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Last pushed

Jul 01, 2025

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